1-6. (canceled)
7. A printing method comprising:
scanning a medium, shaped in a disk shape having a hole portion in the middle thereof and disposed on a document table;
recognizing a non-printing region on data obtained by scanning the medium in accordance with the kind of a print medium to be printed;
executing an image processing, processing the data corresponding to the non-printing region as a non-printing region on the print medium and obtaining a processed data; and
printing the processed data on the print medium.
8. The printing method according to claim 7, wherein each of the medium and the print medium is a CD-R or a DVD-R.
9. The printing method according to claim 8, wherein the print medium is determined by setting a CD-R scan-print mode or a DVD-R scan-print mode.
10. The printing method according to claim 7, wherein the non-printing region on data is recognized based on the size of the medium in length and width derived from the data obtained by scanning the medium and information of a non-printing region prepared in accordance with the kind of the print medium.
11. The printing method according to claim 10, wherein the information of the non-printing region is stored in a ROM.
12. The printing method according to claim 7, wherein the non-printing region on the data includes a region corresponding to at least one of a shadow portion of an edge portion of the medium, the middle hole portion, and a part of the document table placed outside the medium.
13. The printing method according to claim 7, wherein the scanning step includes a first scanning step to judge the position of the medium disposed on the document table and a second scanning step to recognize the non-printing region on the data.
14. A printing method used in a printing apparatus which can scan a disk-shaped medium having a hole portion in the middle thereof on a document table and print scanned data on a print medium, the printing method comprising:
determining a non-printing region from scanned data in accordance with the kind of the print medium to create a printed data;
printing the printed data on the print medium.
15. The printing method according to claim 14, wherein each of the medium and the print medium is a CD-R or a DVD-R.
16. The printing method according to claim 14, wherein the non-printing region is determined by comparing the size of the medium obtained from the scanned data with information of a non-printing region prepared in accordance with the kind of the print medium.
17. The printing method according to claim 14, wherein the non-printing region includes a region corresponding to at least one of a shadow portion of an edge portion of the medium, the middle hole portion, and a part of the document table placed outside the medium.
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 method for computer-aided segmentation of an environment into individual objects, in particular of a wood into individual trees, in which
signals (SIG_R) which are backscattered by the objects are recorded by measurement technology, with the backscattered signals (SIG_R) resulting from the irradiation of the environment to be segmented with electromagnetic radiation;
spatial co-ordinates (x, y, z) of points which cause the backscattering and represent the object parts (X1, X2, . . . , X5) are determined from the backscattered signals (SIG_R), and a feature vector (f) is assigned to each of the points (P; P1, P2), which feature vector comprises at least the spatial co-ordinates (x, y, z) of the point in question (P; P1, P2);
a distance measure (d) is determined for each of the feature vectors (f), which represents a similarity between the feature vectors (f) of two points (P; P1, P2);
the feature vectors (f) assigned to the points (P; P1, P2) are allocated to disjoint segments (A, B) in such a manner that a cost function (E) which takes into account the distance measures (d) of all the feature vectors (f) to each other is minimised, as a result of which the segmentation of the environment into individual objects is provided.
2. The method according to claim 1, in which the electromagnetic radiation is generated by coherent laser beams.
3. The method according to claim 2, in which the electromagnetic radiation is generated by a full waveform laser scanner, wherein complete recording of a respective full waveform signal which is backscattered by the points (P; P1, P2) takes place, from which signal at least the co-ordinates (x, y, z) of a respective point (P; P1, P2) are determined.
4. The method according to claim 3, in which the full waveform signal is decomposed into a series of Gaussian functions in order to determine the backscattered points (P; P1, P2).
5. The method according to claim 4, in which at least one further point-related feature (W, I) is determined for each point from the temporal profile of the energy of the backscattered signal (SIG_R), which feature is added to the allocated feature vector (d).
6. The method according to claim 5, in which the intensity (I) andor the width (W) of a signal pulses which is allocated to a point (P; P1, P2) is determined as the at least one further point-related feature.
7. The method according to one of the preceding claims, in which the emitting of the electromagnetic radiation andor the recording by measurement technology of the backscattered signals takes place in an airborne manner by means of flights, in a satellite-aided manner or terrestrially.
8. The method according to one of the preceding claims, in which the distance measure (d) is determined by the application of a norm to the feature vectors (f) of two points (P; P1, P2).
9. The method according to one of claims 1 to 7, in which the distance measure (d) is determined by combining at least two distance measures (F, X, Z, G) which are weighted using a respective parameter and differ from each other, wherein the differing distance measures (F, X, Y, Z) assess similaritiesdistances in the at least one point-related feature and spatial distances of the points, in particular in the x and y directions as well as in the z direction, differently.
10. The method according to one of the preceding claims, in which a clustering method is used for minimising the global cost function.
11. The method according to one of claims 1 to 9, in which a graph-based method is used for minimising the global cost function, in which a graph consisting of the points as nodes and the distance measures (d) between the points (P; P1, P2) as edges is formed.
12. The method according to claim 11, in which the graph-based NCut measure is used, wherein the cost function is minimised by the Normalised-Cut method.
13. The method according to claim 11, in which the cost function is minimised by means of a graph cut method, wherein a flux between two segments to be formed is maximised and the flux represents the sum of all the edges between nodes of the two subgraphs to the defined.
14. The method according to one of the preceding claims, in which the number of the resulting segments is defined by means of one or a plurality of parameters.
15. The method according to one of the preceding claims, in which the segments are iteratively further decomposed into subsegments as far as a termination criterion.
16. The method according to one of the preceding claims, in which the environment is divided into a predefined spatial grid of voxels and the points (P; P1, P2) are in each case assigned to one of the voxels, wherein points which lie in the same voxel are combined.
17. The method according to one of the preceding claims, in which for at least some of the points (P; P1, P2) at least one further feature is added to the respective feature vectors (f) as a measure which is calculated from the point-related features (W, I) of other points (P; P1, P2) from a local neighbourhood.
18. The method according to claim 17, in which the measure is defined locally for each of the points (P; P1, P2) by a core-based spatial filtering over all the points (P; P1, P2).
19. The method according to claim 17 or 18, in which known knowledge about the objects is added as further information to the feature vectors and is taken into account by means of a further distance measure.
20. The method according to one of the preceding claims, in which trees in a wood are segmented as the objects.
21. The method according to claim 20, in which positions of tree trunks are determined by defining vertical lines in the set of points (P; P1, P2).
22. A computer program product which can be loaded directly into the internal memory of a digital computer and comprises software code sections with which the steps according to one of the preceding claims are carried out when the product runs on a computer.
23. A device for computer-aided segmentation of an environment into individual objects, in particular of a wood into individual trees, comprising
a first means for recording signals (SIG_R) which are backscattered by the objects by measurement technology, wherein the backscattered signals (SIG_R) result from the irradiation of the environment to be segmented with electromagnetic radiation;
a second means for determining spatial co-ordinates (x, y, z) of points which cause the backscattering and represent the object parts (X1, X2, . . . , X5) from the backscattered signals (SIG_R), wherein a feature vector (f) can be assigned by the second means to each of the points (P; P1, P2), which feature vector comprises at least the spatial co-ordinates (x, y, z) of the point in question (P; P1, P2);
a third means for determining a distance measure (d) for each of the feature vectors (f), which represents a similarity between the feature vectors (f) of two points (P; P1, P2);
a fourth means for allocating the feature vectors (f) assigned to the points (P; P1, P2) to disjoint segments (A, B) in such a manner that a cost function (E) which takes into account the distance measures (d) of all the feature vectors (f) to each other can be minimised, as a result of which the segmentation of the environment into individual objects is provided.