Claims Analysis
Total Claims: 5
Claim 1
Independent Claim
199 words
A method of detecting a disparity between stereo images, comprising the steps of: dividing each of first and second images IL and IR into a plurality of blocks each having a size of M×L pixels; matching ternary-valued frequency component images of said images IL and IR; comparing pixels in a micro region defined by a one-dimensional window set on said first image IL with pixels in a designated micro region on said second image IR; evaluating a similarity between two micro regions using the following equation: Εall=Σβk(PN)k+Σγk(ZN)k where PN represents a total number of pixels having an evaluation result "P" while ZN represents a total number of pixels having an evaluation result "Z", and βk and γk represent weighting factors; searching a first region having a most highest similarity and a second region having a second highest similarity in a concerned block; specifying a first candidate disparity as a disparity corresponding to said first region, and a second candidate disparity as a disparity corresponding to said second region; creating a histogram based on said first and second candidate disparities; and determining a valid disparity of said concerned block as a disparity corresponding to a peak position of said histogram.
Claim 2
Independent Claim
199 words
A method of detecting a disparity between stereo images, comprising the steps of: dividing each of first and second images IL and IR into a plurality of blocks each having a size of M×L pixels; matching ternary-valued frequency component images of said images IL and IR; comparing pixels in a micro region defined by a one-dimensional window set on said first image IL with pixels in a designated micro region on said second image IR; evaluating a similarity between two micro regions using the following equation: Εall=Σβk(PN)k+Σγk(ZN)k where PN represents a total number of pixels having an evaluation result "P" while ZN represents a total number of pixels having an evaluation result "Z", and βk and γk represent weighting factors; searching a first region having a most highest similarity and a second region having a second highest similarity in a concerned block; specifying a first candidate disparity as a disparity corresponding to said first region, and a second candidate disparity as a disparity corresponding to said second region; creating a histogram based on said first and second candidate disparities; and determining a valid disparity of said concerned block as a disparity corresponding to a peak position of said histogram.
Claim 3
Dependent Claim
69 words
The method defined by claim 1, wherein said first image IL is designated as a reference image, a one-dimensional window capable of encompassing N pixels therein is set on the ternary-valued frequency component image of said first image IL, and a matching region having the same ternary-value pattern as said N pixels in said one-dimensional window is searched from the ternary-valued frequency component image of said second image IR.
Claim 4
Dependent Claim
94 words
The method defined by claim 1, wherein one of said first and second images IL and IR is designated as a reference image, a plurality of one-dimensional windows are set on the entire surface of said ternary-valued frequency component image of said reference image through a scanning operation along an epipolar line, so that said one-dimensional windows are successively overlapped at the same intervals of N/2 when each of said one-dimensional windows has a size equivalent to N pixels, and a matching operation is carried out with respect to each of said one-dimensional windows.
Claim 5
Dependent Claim
81 words
The method defined by claim 1, wherein said valid disparity is calculated as a sub-pixel level parity corresponding to an intersecting point of a first straight line crossing two points (di-1, hi-1), (di, hi) and a second straight line crossing a point (di+1, hi+1) with a gradient symmetrical with said first straight line, where di-1, di, di+1 represent disparities near the peak position of said histogram and hi-1, hi, hi+represent the number of occurrences of said disparities di-1, di, di+1 respectively.