Pattern characteristic extraction method and device for the same

• US 20050201595A1
• Filed: 07/04/2003
• Published: 09/15/2005
• Est. Priority Date: 07/16/2002
• Status: Abandoned Application

• Current Assignee: NEC Corporation
• Original Assignee: NEC Corporation
• Inventors: Kamei, Toshio
• Application Number:
  US10/512,194
• Publication Number:
  US 20050201595A1
• Time in Patent Office: Days
• US Class Current: 382/118
• CPC Class Codes: G06F 18/2132 based on discrimination criteria, e.g. discriminant analysis
• CPC Class Codes: G06V 10/7715 Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods
• CPC Class Codes: G06V 40/169 Holistic features and representations, i.e. based on the facial image taken as a whole
• CPC Class Codes: G06V 40/171 Local features and components; Facial parts eye characteristics G06V40/18; Occluding parts, e.g. glasses; Geometrical relationships

Abstract

An input pattern feature amount is decomposed into element vectors. For each of the feature vectors, a discriminant matrix obtained by discriminant analysis is prepared in advance. Each of the feature vectors is projected into a discriminant space defined by the discriminant matrix and the dimensions are compressed. According to the feature vector obtained, projection is performed again by the discriminant matrix to calculate the feature vector, thereby suppressing reduction of the feature amount effective for the discrimination and performing effective feature extraction.

Claims

1-22. -22. (canceled)

23. A pattern feature extraction method comprising the steps of

extracting a plurality of input vectors from an input pattern,

projecting the input vectors to obtain projection vectors by using basis matrices respectively corresponding to the input vectors, and

projecting, using a discriminant matrix corresponding to a joint vector, the joint vector obtained by combining a plurality of projection vectors, thereby extracting a feature of the input pattern.

26. A pattern feature extraction method according to claim 23, characterized in that the basis matrices corresponding to the input vectors serve as discriminant matrices for the input vectors.

29. A pattern feature extraction method according to claim 23, characterized in that the basis matrices corresponding to the input vectors are basis matrices specified by transformation matrices for extracting principal component vectors of the input vectors and by discriminant matrices for the principal component vectors.

32. A pattern feature extraction method according to claim 23, characterized in that the step of extracting input vectors comprises the step of extracting vectors whose elements are pixel values obtained from sample points in each sample point set for each of a plurality of predetermined sample point sets in an image serving as an input pattern.

35. A pattern feature extraction method according to claim 32, characterized in that the sample point set comprises a set having as sample points pixels in partial images obtained from a local region of the image, thereby extracting a feature of the image.

36. A pattern feature extraction method according to claim 32, characterized in that the sample point set comprises a set having as sample points pixels in each reduced image obtained from the image, thereby extracting a feature of the image.

37. A pattern feature extraction method according to claim 23, characterized in that the step of extracting input vectors comprises the step of extracting as input vectors feature amounts calculated from each local region for each of a plurality of local regions of the image serving as the input pattern.

40. A pattern feature extraction method according to claim 23, characterized in that the step of extracting input vectors comprises the steps of Fourier-transforming the image serving as the input pattern, extracting Fourier spectrum vectors as the input vectors from a Fourier spectrum of the image, and extracting Fourier amplitude vectors as the input vectors from a Fourier amplitude spectrum of the image, thereby extracting a feature of the image.

43. A pattern feature extraction method according to claim 40, characterized in that a plurality of partial images or reduced images are extracted from the image, and Fourier spectrum vectors or Fourier amplitude vectors of the partial images or reduced images are extracted to extract a feature of the image.

24. A pattern feature extraction method comprising the steps of extracting a plurality of input vectors from an input pattern, projecting the input vectors to obtain projection vectors by using basis matrices respectively corresponding to the input vectors, normalizing the projection vectors to obtain normalized vectors, and projecting, using a discriminant matrix corresponding to a joint vector, the joint vector obtained by combining a plurality of normalized vectors, thereby extracting a feature of the input pattern.

27. A pattern feature extraction method according to claim 24, characterized in that the basis matrices corresponding to the input vectors serve as discriminant matrices for the input vectors.

30. A pattern feature extraction method according to claim 24, characterized in that the basis matrices corresponding to the input vectors are basis matrices specified by transformation matrices for extracting principal component vectors of the input vectors and by discriminant matrices for the principal component vectors.

33. A pattern feature extraction method according to claim 24, characterized in that the step of extracting input vectors comprises the step of extracting vectors whose elements are pixel values obtained from sample points in each sample point set for each of a plurality of predetermined sample point sets in an image serving as an input pattern.

38. A pattern feature extraction method according to claim 24, characterized in that the step of extracting input vectors comprises the step of extracting as input vectors feature amounts calculated from each local region for each of a plurality of local regions of the image serving as the input pattern.

41. A pattern feature extraction method according to claim 24, characterized in that the step of extracting input vectors comprises the steps of Fourier-transforming the image serving as the input pattern, extracting Fourier spectrum vectors as the input vectors from a Fourier spectrum of the image, and extracting Fourier amplitude vectors as the input vectors from a Fourier amplitude spectrum of the image, thereby extracting a feature of the image.

25. A pattern feature extraction method including the steps of extracting a plurality of input vectors from an input pattern and projecting the input vectors to obtain projection vectors, thereby extracting a feature of the input pattern, characterized in that in the step of projecting the input vectors to obtain projection vectors, the input vectors are projected using a transformation matrix specified by basis matrices respectively corresponding to the input vectors and by a discriminant matrix corresponding to a joint vector obtained by combining projection vectors respectively obtained by projecting the input vectors using the basis matrices.

28. A pattern feature extraction method according to claim 25, characterized in that the basis matrices corresponding to the input vectors serve as discriminant matrices for the input vectors.

31. A pattern feature extraction method according to claim 25, characterized in that the basis matrices corresponding to the input vectors are basis matrices specified by transformation matrices for extracting principal component vectors of the input vectors and by discriminant matrices for the principal component vectors.

34. A pattern feature extraction method according to claim 25, characterized in that the step of extracting input vectors comprises the step of extracting vectors whose elements are pixel values obtained from sample points in each sample point set for each of a plurality of predetermined sample point sets in an image serving as an input pattern.

39. A pattern feature extraction method according to claim 25, characterized in that the step of extracting input vectors comprises the step of extracting as input vectors feature amounts calculated from each local region for each of a plurality of local regions of the image serving as the input pattern.

42. A pattern feature extraction method according to claim 25, characterized in that the step of extracting input vectors comprises the steps of Fourier-transforming the image serving as the input pattern, extracting Fourier spectrum vectors as the input vectors from a Fourier spectrum of the image, and extracting Fourier amplitude vectors as the input vectors from a Fourier amplitude spectrum of the image, thereby extracting a feature of the image.

44. A pattern feature extraction apparatus comprising vector extraction means for extracting a plurality of input vectors from an input pattern, basis matrix storage means for storing basis matrices respectively corresponding to the input vectors, linear transformation means for projecting the input vectors to obtain projection vectors using the basis matrices stored in said basis matrix storage means, discriminant matrix storage means for storing a discriminant matrix corresponding to a joint vector obtained by combining a plurality of projection vectors obtained by said linear transformation means, and second linear transformation means for projecting, using the discriminant matrix stored in said discriminant matrix storage means, the joint vector obtained by combining the plurality of projection vectors, thereby extracting a feature of the input pattern.

45. A pattern feature extraction apparatus comprising vector extraction means for extracting a plurality of input vectors from an input pattern, basis matrix storage means for storing basis matrices respectively corresponding to the input vectors, linear transformation means for projecting the input vectors to obtain projection vectors using the basis matrices stored in said basis matrix storage means, normalization means for normalizing the projection vectors to obtain normalized vectors, discriminant matrix storage means for storing a discriminant matrix corresponding to a joint vector obtained by combining a plurality of normalized vectors obtained by said normalization means, and second linear transformation means for projecting, using the discriminant matrix stored in said discriminant matrix storage means, the joint vector obtained by combining the plurality of normalized vectors, thereby extracting a feature of the input pattern.

46. A pattern feature extraction apparatus comprising vector extraction means for extracting a plurality of input vectors from an input pattern, basis matrix storage means for storing basis matrices respectively corresponding to the input vectors, and linear transformation means for projecting the input vectors using the transformation matrices stored in said transformation matrix storage means, thereby extracting a feature of the input pattern, characterized in that the transformation matrices stored in said transformation matrix storage means comprise transformation matrices specified by basis matrices respectively corresponding to the input vectors and the discriminant matrix corresponding to the joint vector obtained by combining the plurality of projection vectors obtained by projecting the input vectors using the basis matrices.

47. A computer-readable storage medium which stores a program for allowing a computer to execute pattern feature extraction for extracting a feature of an input pattern, characterized in that the program comprises a program which executes a function of extracting a plurality of input vectors from an input pattern, a function of projecting the input vectors to obtain projection vectors using basis matrices respectively corresponding to the input vectors, and a function of projecting, using a discriminant matrix corresponding to a joint vector, the joint vector obtained by combining the projection vectors.

48. A computer-readable storage medium which stores a program for allowing a computer to execute pattern feature extraction for extracting a feature of an input pattern, characterized in that the program comprises a program which executes a function of extracting a plurality of input vectors from an input pattern, a function of projecting the input vectors to obtain projection vectors using basis matrices respectively corresponding to the input vectors, a function of normalizing the projection vectors to obtain normalized vectors, and a function of projecting, using a discriminant matrix corresponding to a joint vector, the joint vector obtained by combining the normalized vectors.

49. A computer-readable storage medium which stores a program for allowing a computer to execute pattern feature extraction for extracting a feature of an input pattern by executing a function of extracting a plurality of input vectors from the input pattern and a function of projecting the input vectors, characterized in that the function of projecting the input vectors comprises a function of projecting the input vectors by using a transformation matrix specified by basis matrices respectively corresponding to the input vectors and by a discriminant matrix corresponding to a joint vector obtained by combining the plurality of projection vectors obtained by projecting the input vectors using the basis matrices.

50. A pattern feature extraction method characterized by comprising the steps of segmenting an input image using different segmentation numbers to obtain a plurality of block images and the step of extracting Fourier amplitudes of the block images, thereby extracting a feature amount of the input image.

51. A pattern feature extraction method according to claim 50, characterized by comprising the steps of scanning the Fourier amplitudes to extract multiblock Fourier amplitude vectors, and projecting the multiblock Fourier amplitude vectors using basis matrices to obtain projection vectors.

52. A pattern feature extraction method according to claim 51, characterized by further comprising the step of normalizing the projection vectors to obtain normalized vectors.

53. A pattern feature extraction method according to claim 51, characterized in that the basis matrices comprise basis matrices specified by transformation matrices for extracting principal component vectors of the multiblock Fourier amplitude vectors and by discriminant matrices corresponding to the principal component vectors.

54. A pattern feature extraction method according to claim 50, characterized in that in the step of obtaining the plurality of block images, at least one entire image having the entire input image as one block image, four block images obtained by segmenting the entire input image into four blocks, and 16 block images obtained by segmenting the input image into 16 blocks are obtained.

55. A pattern feature extraction method characterized by comprising the steps of

obtaining a Fourier spectrum vector by calculating a Fourier spectrum for an input normalized image by using a predetermined calculation expression,

extracting a multiblock Fourier amplitude vector from a Fourier amplitude of a partial image of the normalized image,

performing feature vector projection of the Fourier spectrum vector and the multiblock intensity vector by using a basis matrix, thereby obtaining respective normalized vectors,

combining the normalized vectors to obtain a coupled Fourier vector and using a second basis matrix to transform the coupled value into a projection vector, and

extracting a Fourier feature by quantizing the projection vector.