Author: claimsbot

1. An information input apparatus comprising:
a light emitter for irradiating an object with light;
an area image sensor for outputting a difference between charges received by light-receiving cells arranged in an array pattern from a reflected light of the object caused by said light emitter irradiating the object with light;
a timing signal generator for generating a timing signal comprised of a pulse’signal or a modulation signal for controlling an intensity of light of said light emitter;
a control signal generator for generating a control signal for individually controlling light-receiving timings of the light-receiving cells of said area image sensor on the basis of the timing signal from said timing signal generator; and
image processing means for extracting a reflected light image of the object from the difference outputted from said area image sensor.
2. The apparatus according to claim 1, wherein said area image sensor separately receives light in units of even lines or odd lines.
3. An information input apparatus comprising:
a timing signal generator for generating a timing signal comprised of a pulse signal or a modulation signal;
a light emitter for emitting light, an intensity of which changes on the basis of the timing signal from said timing signal generator;
first light-receiving section for receiving light emitted by said light emitter and reflected by an object in synchronism with the timing signal from said timing signal generator; and
second light-receiving section for receiving light other than the light emitted by said light emitter and reflected by the object.
4. The apparatus according to claim 3, further comprising:
first imaging means for imaging the object reflected light received by said first light-receiving means; and
second imaging means for imaging the light other than the object reflected light and received by said second light-receiving means.
5. The apparatus according to claim 3, further comprising:
light splitting means for splitting light into the object reflected light and the light other than the object reflected light.
6. The apparatus according to claim 1, wherein said control signal generator selectively outputs a control signal for controlling said area image sensor to sense a reflected light image of the object, and a control signal for controlling said area image sensor to sense a light image by the light other than the reflected light.
7. The apparatus according to claim 6, further comprising:
a pass filter for passing only light emitted by said light emitter;
a cut filter for intercepting light emitted by said light emitter; and
means for selecting one of the two filters upon passing light to be sensed.
8. The apparatus according to claim 6, further comprising:
a pass filter for passing only light emitted by said light emitter;
a cut filter for intercepting light emitted by said light emitter; and
switching means for selecting one of said pass filter and said cut filter in synchronism with the timing signal from said timing signal generator.
9. The apparatus according to claim 6, further comprising:
light splitting section for splitting light into the object reflected light and the light other than the object reflected light;
a selector for selecting whether the light is to be passed or intercepted on optical paths of the split light beams; and
a synthesizing section for synthesizing the two light beams split by said light splitting section.
10. The apparatus according to claim 9, wherein said light splitting section has an element for selecting one of a state wherein only a light source wavelength is passed and a state wherein only visible light is passed.
11. The apparatus according to claim 9, wherein said light splitting section includes:
a first element for selecting one of a state wherein only a light source wavelength is passed and a state wherein all light components are passed; and
a second element for selecting one of a state wherein only visible light is passed and a state wherein all light components are passed.
12. The apparatus according to claim 1, wherein the light-receiving cells of said area image sensor include cells for sensing a reflected light image, and cells for sensing a light image other than the reflected light.
13. The apparatus according to claim 3, wherein the light-receiving cells of said area image sensor include cells for sensing a reflected light image, and cells for sensing a light image other than the reflected light.
14. An information input method comprising the steps of:
generating a pulse signal or modulation signal;
generating, on the basis of the pulse or modulation signal, a control signal for separately controlling light-receiving timings of light-receiving cells of an area image sensor for obtaining a difference between charges received by light-receiving cells which are arranged in an array pattern;
emitting light, an intensity of which changes on the basis of the generated control signal; and
detecting a light image reflected by an object of the emitted light.
15. An information input method comprising the steps of:
generating a pulse signal or modulation signal;
emitting light, an intensity of which changes on the basis of the pulse or modulation signal; and
receiving light reflected by an object of the emitted light and light other than the reflected light in synchronism with the pulse or modulation signal.
16. An article of manufacture comprising:
a computer usable medium having computer readable program code means embodied therein for causing an area image sensor for obtaining a difference between charges received by light-receiving cells which are arranged in an array pattern to be controlled, the computer readable program code means in said article of manufacture comprising:
computer readable program code means for causing a computer to generate a pulse signal or a modulation signal;
computer readable program code means for causing a computer to generate a control signal for separately controlling light-receiving timings of the light-receiving cells of said area image sensor on the basis of the pulse or modulation signal;
computer readable program code means for causing a computer to cause a light emitter to emit light, an intensity of which changes on the basis of the generated pulse signal or modulation signal; and
computer readable program code means for causing a computer to extract a light image reflected by an object of the emitted light from the difference outputted from said area image sensor.
17. An article of manufacture comprising:
a computer usable medium having computer readable program code means embodied therein for causing an area image sensor for obtaining a difference between charges received by light-receiving cells which are arranged in an array pattern to be controlled, the computer readable program code means in said article of manufacture comprising:
computer readable program code means for causing a computer to generate a pulse signal or a modulation signal;
computer readable program code means for causing a computer to cause a light emitter to emit light, an intensity of which changes on the basis of the pulse or modulation signal; and
computer readable program code means for causing a computer to cause the light-receiving cells to receive light reflected by an object of the emitted light and light other than the reflected light in synchronism with the pulse or modulation signal.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A computer-implemented method for enabling users of computing devices to visually identify the relative trustworthiness of files without having to request separate trustworthiness evaluations of the files by displaying trustworthiness classifications for files as visually overlaid icons, at least a portion of the method being performed by at least one computing device comprising at least one processor, the method comprising:
identifying, at a shell extension within a file manager installed on the computing device:
a first file;
a second file that performs a substantially similar function to the first file;

in response to identifying the first and second files, allowing a user of the computing device to visually compare the trustworthiness of the first and second files without requiring the user to request a separate evaluation of the files’ trustworthiness by:
identifying, at the shell extension:
a first file icon that graphically represents the first file within a file manager interface;
a second file icon that graphically represents the second file within the same file manager interface;

obtaining, at the shell extension:
a first trustworthiness classification assigned to the first file that identifies the trustworthiness of the first file;
a second trustworthiness classification assigned to the second file that identifies the trustworthiness of the second file;

visually overlaying, at the shell extension:
the first file icon with a first trustworthiness icon that graphically represents the trustworthiness classification assigned to the first file;
the second file icon with a second trustworthiness icon that graphically represents the second trustworthiness classification assigned to the second file.
2. The computer-implemented method of claim 1, wherein the first and second trustworthiness classifications assigned to the first and second files indicate that at least one of:
the first or second file’s trustworthiness is unknown;
the first or second file is untrustworthy;
the first or second file is trustworthy.
3. The computer-implemented method of claim 1,
wherein the first trustworthiness icon visually overlaid on the first file icon is juxtaposed with the second trustworthiness icon visually overlaid on the second file icon.
4. The computer-implemented method of claim 1, wherein:
visually overlaying the first file icon with the first trustworthiness icon comprises generating a single overlaid file icon that comprises both the first file icon and the first trustworthiness icon;
visually overlaying the second file icon with the second trustworthiness icon comprises generating a single overlaid file icon that comprises both the second file icon and the second trustworthiness icon.
5. The computer-implemented method of claim 1, wherein the first and second trustworthiness classifications assigned to the first and second files comprise information that identifies a reputation of the first or second file within a community.
6. The computer-implemented method of claim 1, wherein obtaining the first and second trustworthiness classifications assigned to the first and second files comprises receiving the first and second trustworthiness classifications from a reputation service.
7. The computer-implemented method of claim 1, wherein identifying the first and second files comprises identifying files that are created as part of an installation process.
8. The computer-implemented method of claim 1, wherein identifying the first and second files comprises identifying a directory comprising the first and second files and analyzing contents of the directory prior to causing the contents of the directory to be displayed within the file manager interface.
9. A system for enabling users of computing devices to visually identify the relative trustworthiness of files without having to request separate trustworthiness evaluations of the files by displaying trustworthiness classifications for files as visually overlaid icons, the system comprising:
an identification module, a classification module, and an overlay module collectively programmed to:
identify, at a shell extension within a file manager installed on a computing device;
a first file;
a second file that performs a substantially similar function to the first file;

in response to identifying the first and second files, allowing a user of the computing device to visually compare the trustworthiness of the first and second files without requiring the user to request a separate evaluation of the files’ trustworthiness by:
identifying, at the shell extension:
a first file icon that graphically represents the first file within a file manager interface on the computing device;
a second file icon that graphically represents the second file within the same file manager interface;

obtaining, at the shell extension:
a first trustworthiness classification assigned to the first file that identifies the trustworthiness of the first file;
a second trustworthiness classification assigned to the second file that identifies the trustworthiness of the second file;

visually overlaying, at the shell extension;
the first file icon with a first trustworthiness icon that graphically represents the first trustworthiness classification assigned to the first file;
the second file icon with a second trustworthiness icon that graphically represents the second trustworthiness classification assigned to the second file;
at least one processor configured to execute the identification module, the classification module, and the overlay module.
10. The system of claim 9, wherein the first and second trustworthiness classifications assigned to the first and second files indicate that at least one of:
the first or second file’s trustworthiness is unknown;
the first or second file is untrustworthy;
the first or second file is trustworthy.
11. The system of claim 9,
wherein the first trustworthiness icon visually overlaid on the first file icon is juxtaposed with the second trustworthiness icon visually overlaid on the second file icon.
12. The system of claim 9, wherein the overlay module:
visually overlays the first file icon with the first trustworthiness icon by generating a single overlaid file icon that comprises both the first file icon and the first trustworthiness icon;
visually overlays the second file icon with the second trustworthiness icon by generating a single overlaid file icon that comprises both the second file icon and the second trustworthiness icon.
13. The system of claim 9, wherein the first and second trustworthiness classifications assigned to the first and second files comprise information that identifies a reputation of the first or second file within a community.
14. The system of claim 9, wherein the classification module is further programmed to receive the first and second trustworthiness classifications from a reputation service.
15. The system of claim 9, wherein the shell extension is provided as part of a third-party software package.
16. The system of claim 9, wherein the first and second trustworthiness classifications assigned to the first and second files are represented by a numeric score that identifies the first and second files’ trustworthiness.
17. A non-transitory computer-readable-storage medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to:
identify, at a shell extension within a file manager installed on the computing device:
a first file;
a second file that performs a substantially similar function to the first file;

in response to identifying the first and second files, allowing a user of the computing device to visually compare the trustworthiness of the first and second files without requiring the user to request a separate evaluation of the files’ trustworthiness by:
identifying, at the shell extension;
a first file icon that graphically represents the first file within a file manager interface on the computing device;
a second file icon that graphically represents the second file within the same file manager interface;

obtaining, at the shell extension;
a first trustworthiness classification assigned to the first file that identifies the trustworthiness of the first file;
a second trustworthiness classification assigned to the second file that identifies the trustworthiness of the second file;

visually overlaying, at the shell extension;
the first file icon with a first trustworthiness icon that graphically represents the first trustworthiness classification assigned to the first file;
the second file icon with a second trustworthiness icon that graphically represents the second trustworthiness classification assigned to the second file.
18. The non-transitory computer-readable-storage medium of claim 17, wherein the first and second trustworthiness classifications assigned to the first and second files indicate that at least one of:
the first or second file’s trustworthiness is unknown;
the first or second file is untrustworthy;
the first or second file is trustworthy.
19. The non-transitory computer-readable-storage medium of claim 17,
wherein the first trustworthiness icon visually overlaid on the first file icon is juxtaposed with the second trustworthiness icon visually overlaid on the second file icon.
20. The non-transitory computer-readable-storage medium of claim 17, wherein:
the first file icon is visually overlaid with the first trustworthiness icon by generating a single overlaid file icon that comprises both the first file icon and the first trustworthiness icon;
the second file icon is visually overlaid with the second trustworthiness icon by generating a single overlaid file icon that comprises both the second file icon and the second trustworthiness icon.

1. An image processing apparatus, comprising:
a connection unit that receives image data to be printed and image information on a type of the image data from an external device; and
a pseudo-halftone processing unit that converts the image data into pseudo-halftone image data, wherein,
in response to a determination that the image information received from the external device indicates that the type of the image data is a point-of-purchase advertising image based on whether the image data includes one of a product name and a price,
the pseudo- halftone processing unit performs a pseudo-halftone processing on the image data at a quantization level of three or more bits on a pixel and takes a growth order causing all pixels in a high-density area to grow averagely;
the pseudo-halftone processing unit performs another pseudo-halftone processing on the image data, in response to a determination that the type of the image data is not the point-of-purchase advertising image, and
the another pseudo-halftone processing is different from the pseudo-halftone processing performed in response to the determination that the type of the image data is the point-of-purchase advertising image.
2. The image processing apparatus according to claim 1, wherein the pseudo-halftone processing unit performs the pseudo-halftone processing based on a dithering.
3. The image processing apparatus according to claim 1, wherein the image data is four-color image data including cyan, magenta, yellow, and black.
4. An image forming apparatus comprising an image processing apparatus according to claim 1.
5. The image forming apparatus according to claim 4, further comprising:
an image analyzing unit that analyzes the image data, and makes the determination whether the type of the image data is the point-of-purchase advertising image; and
a sending unit that sends a result of the determination to the connection unit.
6. The image forming apparatus according to claim 5, wherein the image analyzing unit makes the determination based on whether the one of the product name and the price is included in the image data.
7. The image forming apparatus according to claim 4, further comprising: a photosensitive element as an image carrier;
a laser-light emitting unit as an exposure unit for forming an electrostatic latent image on the photosensitive element; and
a control unit that controls the laser-light emitting unit based on data obtained by performing the pseudo-halftone processing on the image data.
8. An image processing apparatus, comprising:
a connection unit that receives image data to be printed and image information on a type of the image data from an external device; and
a pseudo-halftone processing unit that converts the image data into pseudo-halftone image data, wherein,
in response to a determination that the image information received from the external device indicates that the type of the image data is a point-of-purchase advertising image based on whether the image data includes one of a product name and a price,
the pseudo- halftone processing unit performs a pseudo-halftone processing on the image data at a quantization level of three or more bits on a pixel, takes a growth order causing pixels in a low-density area to grow pixel-by-pixel up to an intermediate quantization level, and takes a growth order causing all pixels in a high-density area to grow averagely;
the pseudo-halftone processing unit performs another pseudo-halftone processing on the image data, in response to a determination that the type of the image data is not the point-of-purchase advertising image, and
the another pseudo-halftone processing is different from the pseudo-halftone processing performed in response to the determination that the type of the image data is the point-of-purchase advertising image.
9. The image processing apparatus according to claim 8, wherein the pseudo-halftone processing unit performs the pseudo-halftone processing based on a dithering.
10. The image processing apparatus according to claim 9, wherein in the low-density area, the pseudo-halftone processing unit performs the pseudo-halftone processing with a dot pattern.
11. The image processing apparatus according to claim 9, wherein in the low-density area, the pseudo-halftone processing unit performs the pseudo-halftone processing with a line pattern.
12. The image processing apparatus according to claim 8, wherein the image data is four-color image data including cyan, magenta, yellow, and black.
13. An image forming apparatus comprising an image processing apparatus according to claim 8.
14. The image forming apparatus according to claim 13, further comprising: an image analyzing unit that analyzes the image data, and makes the determination whether the type of the image data is the point-of-purchase advertising image; and
a sending unit that sends a result of the determination to the connection unit.
15. The image forming apparatus according to claim 14, wherein the image analyzing unit makes the determination based on whether the one of the product name and the price is included in the image data.
16. The image forming apparatus according to claim 13, further comprising:
a photosensitive element as an image carrier;
a laser-light emitting unit as an exposure unit for forming an electrostatic latent image on the photosensitive element; and
a control unit that controls the laser-light emitting unit based on data obtained by performing the pseudo-halftone processing on the image data.
17. A method implemented by an image processing apparatus, the method comprising:
receiving image data to be printed and image information on a type of the image data from an external device;
converting the image data into pseudo-halftone image data;
performing, with the image processing apparatus, a pseudo-halftone processing on the image data at a quantization level of three or more bits on a pixel and taking a growth order causing all pixels in a high-density area to grow averagely, in response to a determination that the image information received from the external device indicates that the type of the image data is a point-of-purchase advertising image based on whether the image data includes one of a product name and a price; and
performing, with the image processing apparatus, another pseudo-halftone processing on the image data, in response to a determination that the type of the image data is not the point-of-purchase advertising image, wherein
the another pseudo-halftone processing is different from the pseudo-halftone processing performed in response to the determination that the type of the image data is the point-of-purchase advertising image.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A media capture device, comprising:
a media capture mechanism;
an audio input receptive of user speech relating to a media capture activity in close temporal relation to the media capture activity;
a plurality of focused speech recognition lexica respectively relating to media capture activities;
a speech recognizer adapted to recognize the user speech based on a selected one of the focused speech recognition lexica;
a media tagger adapted to tag captured media with text generated by said speech recognizer based on close temporal relation between receipt of recognized user speech and capture of the captured media; and
a media annotator adapted to annotate the captured media with a sample of the user speech that is suitable for input to a speech recognizer based on close temporal relation between receipt of the user speech and capture of the captured media.
2. The device of claim 1, further comprising an input receptive of a user identity, wherein said speech recognizer is adapted to recognize user speech based on the user identity.
3. The device of claim 2, wherein said speech recognizer is adapted to employ focused lexica based on the user identity.
4. The device of claim 1, wherein said speech recognizer is adapted to select a lexicon based on the user speech and a predefined heuristic relating to voice tags associated with the lexica.
5. The device of claim 1, further comprising a user interface adapted to permit a user to navigate between and select a lexicon.
6. The device of claim 1, further comprising a media retrieval mechanism adapted to retrieve captured media from memory of the device by matching a tag of the captured media to recognition text generated form user speech received and recognized during a retrieval mode of the device.
7. The device of claim 1, further comprising a media retrieval mechanism adapted to retrieve captured media from memory of the device by matching an annotation of the captured media to user speech received during a retrieval mode of the device using sound similarity metrics to align an annotation with a spoken query.
8. The device of claim 1, further comprising a lexicon editor adapted to supplement a lexicon based on an annotation, letter to sound rules, and user speech corresponding to spelled word input received and recognized during a lexicon edit mode of the device.
9. The device of claim 1, further comprising an external data interface adapted to transmit annotations to a post processor having greater speech recognition capabilities than said device.
10. The device of claim 1, further comprising:
an external data interface receptive of lexicon contents; and
a lexicon editor adapted to store the lexicon contents in device memory.
11. A media tagging system, comprising:
a portable media capture device adapted to capture media, to receive user speech in close temporal relation to a media capture activity, and adapted to annotate captured media with a sample of the user speech that is suitable for input to a speech recognizer based on close temporal relation between receipt of the user speech and capture of the captured media; and
a post processor adapted to receive annotations from the device, perform speech recognition on the annotations, and tag related captured media with text generated during speech recognition performed on the annotations.
12. The system of claim 11, comprising a source of predefined, focused lexica relating to media capture activities and adapted to communicate focused lexica to said media capture device according to device type over a communications network.
13. The system of claim 11, comprising a source of predefined, focused lexica relating to media capture activities and adapted to communicate focused lexica to said post-processor over a communications network.
14. The system of claim 11, comprising a lexicon editor provided to at least one of the device and the post processor and adapted to customize a focused lexicon for a user of the device.
15. The system of claim 11, comprising a mapping module adapted to convert textual tags associated with captured media to alternative textual tags based on predetermined criteria relating to a media capture activity.
16. The system of claim 11, wherein said device is adapted to perform a relatively limited amount of speech recognition on the annotation compared to an amount of speech recognition performed by said post-processor, the relatively limited amount being limited in at least one of time and search space due to at least one of relatively lower processing power and relatively lower memory capacity of said device, and to tag related captured media with recognition text generated during the relatively limited amount of speech recognition.
17. The system of claim 11, wherein said post-processor is receptive of captured media from said device, and is adapted to organize the captured media according to at least one of annotations and textual tags associated with the captured media, including clustering at least one of annotations and textual tags based on at least one of acoustic similarity measures and semantic similarity measures.
18. A media tagging method for use with a media capture device, comprising:
capturing media with the media capture device during a media capture activity conducted by a user of the device;
receiving user speech via an audio input of the device in close temporal relation to the media capture activity;
annotating captured media by storing the captured media in memory of the device in association with a sample of the user speech that is suitable for input to a speech recognizer;
recognizing the user speech with a speech recognizer of the device employing a focused speech recognition lexicon relating to the media capture activity; and
tagging captured media with recognition text generated during recognition of the user speech by storing the captured media in memory of the device in association with the recognition text.
19. The method of claim 18, further comprising selecting a focused speech recognition lexicon relating to the media capture activity from a plurality of focused lexica relating to media capture activities that are stored in memory of the device.
20. The method of claim 19, wherein said step of selecting the focused speech recognition lexicon is based on the user speech and a predefined heuristic relating to voice tags associated with the lexica.
21. The method of claim 19, wherein said step of selecting the focused speech recognition lexicon is based on user navigation of the lexica via a user interface of the device.
22. The method of claim 18, further comprising receiving a user identity, wherein said step of recognizing the user speech is based on the user identity.
23. The method of claim 22, further comprising selecting, based on the user identity, a focused speech recognition lexicon relating to the media capture activity from a plurality of focused lexica relating to media capture activities that are stored in memory of the device.
24. The method of claim 18, further comprising retrieving captured media from memory of the device by matching a tag of the captured media to recognition text generated form user speech received and recognized during a retrieval mode of the device.
25. The method of claim 18, further comprising retrieving captured media from memory of the device by matching an annotation of the captured media to user speech received during a retrieval mode of the device using sound similarity metrics to align an annotation with a spoken query.
26. The method of claim 18, further comprising supplementing a lexicon stored in device memory based on an annotation, letter to sound rules, and user speech corresponding to spelled word input received and recognized during a lexicon edit mode of the device.
27. The method of claim 18, further comprising receiving lexicon contents and storing the lexicon contents in device memory.
28. The method of claim 18, further comprising transferring annotations from the device to a post processor having greater speech recognition capability than the device.
29. The method of claim 28, further comprising:
performing speech recognition on annotations received from the device; and
tagging related captured media with text generated during speech recognition performed on the annotations.
30. The method of claim 28, comprising transferring focused lexica from a source of predefined, focused lexica to the post processor.
31. The method of claim 18, comprising transferring focused lexica from a source of predefined, focused lexica to the device.
32. The method of claim 18, comprising customizing a focused lexicon for a user of the device.
33. The method of claim 18, comprising convert textual tags associated with captured media to alternative textual tags based on predetermined criteria relating to a media capture activity.
34. The method of claim 18, further comprising organizing the captured media according to textual tags associated with the captured media, including clustering textual tags based on semantic similarity measures.
35. The method of claim 18, further comprising organizing the captured media according to annotations associated with the captured media, including clustering annotations based on acoustic similarity measures.