Recognizing text in a multicolor image

Claim 2

A computer-implemented method recognizing text in a multicolor image stored in a computer, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the method comprising: separating the image into multiple blocks; analyzing color distributions of the pixels in each of the blocks; identifying blocks having two main colors; grouping two-color blocks having similar colors into two-color zones; identifying text in the two-color zones; mapping the pixels of each block to a three-dimensional color space; defining, for each two-color block, a cylinder that encloses the pixels, the cylinder having a height and a radius; classifying a block as a text block if the ratio of the radius to the height is less than a predefined value, wherein the text identifying step is performed in the text blocks.

Claim 3

The method of claim 1, further comprising: converting the two colors in each zone to black and white to produce a black and white image.

Claim 4

The method of claim 2, further comprising: performing optical character recognition of the black and white image.

Claim 5

The method of claim 1, wherein the predefined value is approximately 0.35.

Claim 6

The method of claim 1, wherein the image is stored in the computer as a raster of pixels, the method further comprising: representing each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identifying clusters of vectors that point generally in the same directions; and marking blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 7

The method of claim 5, wherein the cluster-identifying step includes: defining sample points on a sphere in the three-dimensional color space; identifying a local maximum of a predefined function at a sample point; and grouping the vectors within a predetermined angle of the sample point into a cluster.

Claim 8

The method of claim 6, wherein the sample points are uniformly distributed on the sphere.

Claim 9

A computer program residing on a computer-readable medium for recognizing text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the computer program comprising instructions for causing the computer to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; and identify text in the two-color zones; map the pixels of each block to a three-dimensional color space; define, for each two-color block, a cylinder that encloses the pixels, the cylinder having a height and a radius; and classify a block as a text block if the ratio of the radius to the height is less than a predefined value, wherein the text is identified in the text blocks.

Claim 10

A computer program residing on a computer-readable medium for recognizing text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the computer program comprising instructions for causing the computer to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; and identify text in the two-color zones; map the pixels of each block to a three-dimensional color space; define, for each two-color block, a cylinder that encloses the pixels, the cylinder having a height and a radius; and classify a block as a text block if the ratio of the radius to the height is less than a predefined value, wherein the text is identified in the text blocks.

Claim 11

The computer program of claim 8, further comprising instructions for causing the computer to: convert the two colors in each zone to black and white to produce a black and white image.

Claim 12

The computer program of claim 9, further comprising instructions for causing the computer to: perform optical character recognition of the black and white image.

Claim 13

The computer program of claim 8, wherein the predefined value is approximately 0.35.

Claim 14

The computer program of claim 8, wherein the image is stored in the computer as a raster of pixels, the computer program further comprising instructions for causing the computer to: represent each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identify clusters of vectors that point generally in the same directions; and mark blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 15

The computer program of claim 12, wherein the cluster-identifying step includes: defining sample points on a sphere in the three-dimensional color space; identifying a local maximum of a predefined function at a sample point; and grouping the vectors within a predetermined angle of the sample point into a cluster.

Claim 16

The computer program of claim 13, wherein the sample points are uniformly distributed on the sphere.

Claim 17

Apparatus to recognize text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the apparatus comprising: storage medium to store the image; and a processor operatively coupled to the storage medium and configured to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; and identify text in the two-color zones; map the pixels of each block to a three-dimensional color space; define, for each two-color block, a cylinder that encloses the pixels, the cylinder having a height and a radius; and classify a block as a text block if the ratio of the radius to the height is less than a predefined value, wherein the text identifying step is performed in the text blocks.

Claim 18

Apparatus to recognize text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the apparatus comprising: storage medium to store the image; and a processor operatively coupled to the storage medium and configured to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; and identify text in the two-color zones; map the pixels of each block to a three-dimensional color space; define, for each two-color block, a cylinder that encloses the pixels, the cylinder having a height and a radius; and classify a block as a text block if the ratio of the radius to the height is less than a predefined value, wherein the text identifying step is performed in the text blocks.

Claim 19

The apparatus of claim 15, wherein the processor is further configured to: convert the two colors in each zone to black and white to produce a black and white image.

Claim 20

The apparatus of claim 15, wherein the image is stored in the computer as a raster of pixels, and wherein the processor is further configured to: represent each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identify clusters of vectors that point generally in the same directions; and mark blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 21

A computer-implemented method recognizing text in a multicolor image stored in a computer, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the method comprising: separating the image into multiple blocks; analyzing color distributions of each of the blocks; identifying blocks having two main colors; grouping two-color blocks having similar colors into two-color zones; identifying text in the two-color zones; representing each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identifying clusters of vectors that point generally in the same directions; and marking blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 22

A computer-implemented method recognizing text in a multicolor image stored in a computer, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the method comprising: separating the image into multiple blocks; analyzing color distributions of each of the blocks; identifying blocks having two main colors; grouping two-color blocks having similar colors into two-color zones; identifying text in the two-color zones; representing each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identifying clusters of vectors that point generally in the same directions; and marking blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 23

The method of claim 18, wherein the cluster-identifying step includes: defining sample points on a sphere in the three-dimensional color space; identifying a local maximum of a predefined function at a sample point; and grouping the vectors within a predetermined angle of the sample point into a cluster.

Claim 24

The method of claim 19, wherein the sample points are uniformly distributed on the sphere.

Claim 25

A computer program residing on a computer-readable medium for recognizing text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the computer program comprising instructions for causing the computer to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; identify text in the two-color zones; represent each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identify clusters of vectors that point generally in the same directions; and mark blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 26

A computer program residing on a computer-readable medium for recognizing text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the computer program comprising instructions for causing the computer to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; identify text in the two-color zones; represent each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identify clusters of vectors that point generally in the same directions; and mark blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 27

The computer program of claim 21, wherein the cluster-identifying step includes: defining sample points on a sphere in the three-dimensional color space; identifying a local maximum of a predefined function at a sample point; and grouping the vectors within a predetermined angle of the sample point into a cluster.

Claim 28

The computer program of claim 22, wherein the sample points are uniformly distributed on the sphere.

Claim 29

Apparatus to recognize text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the apparatus comprising: storage medium to store the image; and a processor operatively coupled to the storage medium and configured to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; identify text in the two-color zones; represent each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identify clusters of vectors that point generally in the same directions; and mark blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.

Claim 30

Apparatus to recognize text in a multicolor image, the multicolor image comprising a plurality of pixels, each pixel having an associated color, the apparatus comprising: storage medium to store the image; and a processor operatively coupled to the storage medium and configured to: separate the image into multiple blocks; analyze color distributions of each of the blocks; identify blocks having two main colors; group two-color blocks having similar colors into two-color zones; identify text in the two-color zones; represent each block as a vector in a three-dimensional color space, the vector originating at a point in a first group of pixels corresponding to a first color and terminating at a point in a second group of pixels corresponding to a second color; identify clusters of vectors that point generally in the same directions; and mark blocks corresponding to clusters that contain more than a predefined number of vectors as text blocks.