Ternary image templates for improved semantic compression
First Claim
1. Apparatus for detecting edge contours approximating a given feature in a pixel matrix representing a given image frame, said apparatus comprising:
- an edge detector for producing an edge map from the pixel matrix, said edge map having a first plurality of edge pixels and a second plurality of non-edge pixels, each pixel in one of said first and second pluralities of pixels having an assigned value of +k and each pixel in the other one of said first and second pluralities of pixels having an assigned value of -k;
a first feature template having a feature pattern including a first and a second feature contour, said first and second feature contours being contiguous with each other and having a plurality of pixels, each pixel in said first feature contour having an assigned value of -2k, each pixel in said second feature contour having an assigned value of +2k, and pixels in said first feature template outside said first and second feature contours having an assigned value of 0k; and
an array processor for calculating sum-and-absolute-difference values between a block of pixels in said first feature template and a corresponding block of pixels on said edge map corresponding to said block of pixels in said first feature template at a given location of said first feature template on said edge map, and for using said sum-and-absolute-difference values to calculate an estimated correlation between edge contours on said edge map and said feature contours in said first feature template as a match metric.
4 Assignments
0 Petitions
Accused Products
Abstract
A method and apparatus for carrying out rapid, block-based SAD search operations for facial ellipses in a CIF videophone image frame are disclosed. A set of search templates, each having an ellipse pattern with two concentric, contiguous perimeters is defined and a set of parameter values are calculated off line for each template: a predetermined subfactor, index number, number of pixels in its dithered perimeter pattern, and first and second match thresholds. The pixels in the lower portion of each perimeter in the pattern are thinned by dithering so as to emphasize the upper contour of the ellipse. Values of +2k for interior perimeter pixels and -2k for exterior pixels in the template are then added to corresponding +k edge pixels and -k non-edge pixels in each search position of the template on a thresholded binary edge map of the image frame. The sum is then normalized and the template and search position producing the best SAD match metric value is identified as a facial area, without requiring symmetry detection.
127 Citations
23 Claims
-
1. Apparatus for detecting edge contours approximating a given feature in a pixel matrix representing a given image frame, said apparatus comprising:
-
an edge detector for producing an edge map from the pixel matrix, said edge map having a first plurality of edge pixels and a second plurality of non-edge pixels, each pixel in one of said first and second pluralities of pixels having an assigned value of +k and each pixel in the other one of said first and second pluralities of pixels having an assigned value of -k; a first feature template having a feature pattern including a first and a second feature contour, said first and second feature contours being contiguous with each other and having a plurality of pixels, each pixel in said first feature contour having an assigned value of -2k, each pixel in said second feature contour having an assigned value of +2k, and pixels in said first feature template outside said first and second feature contours having an assigned value of 0k; and an array processor for calculating sum-and-absolute-difference values between a block of pixels in said first feature template and a corresponding block of pixels on said edge map corresponding to said block of pixels in said first feature template at a given location of said first feature template on said edge map, and for using said sum-and-absolute-difference values to calculate an estimated correlation between edge contours on said edge map and said feature contours in said first feature template as a match metric. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
-
-
12. Apparatus for providing a higher detail level to compression-coded pixels in a part of a given pixel matrix representing a video-image frame, said part including edge contours correlating with contours of a facial ellipse, said apparatus comprising:
-
an edge detector for producing an edge map from the pixel matrix, said edge map having a first plurality of edge pixels and a second plurality of non-edge pixels, each pixel in one of said first and second pluralities of pixels having an assigned value of +k and each pixel in the other one of said first and second pluralities of pixels having an assigned value of -k; template storage apparatus for storing face templates, each of said face templates including an ellipse pattern having a first and a second ellipse contour, said ellipse contours being contiguous with each other, and each said ellipse contour having a plurality of pixels, each pixel in said first ellipse contour having an assigned value of -2k, each pixel in said second ellipse contour having an assigned value of +2k, and pixels in said face template outside said first and second ellipse contours having an assigned value of 0k; an array processor for calculating sets sum-and-absolute-difference values between a block of pixels in each of said face templates and a corresponding block of pixels on said edge map corresponding to said block of pixels in each face template at a given location of said face template on said edge map, for using said sets of sum-and-absolute-difference values to calculate respective estimated correlations between edge contours on said edge map and said ellipse-contours in each face template in a first location on said edge map as a respective first match metric for said respective face template, for using said sets of sum-and-absolute-difference values to calculate respective estimated correlations between edge contours on said edge map and said ellipse-contour pixels in each face template in a second location on said edge map as a second match metric for said respective face template, for determining which of said first and second locations is a best-match location for each face template, said best match location producing a best match metric indicating that said respective best-match location has a closest correlation between said edge contours and said ellipse contours in said respective template, and for determining a best-match face template by comparing respective best match metrics produced by respective best-match locations of said face templates on said edge map; normalizing means for normalizing said best-match metric calculated for each template before determining said best-match face template; a coder for encoding pixels in said video image frame; and control means for locating facial pixels in a part of said image pixel matrix corresponding to edge pixels in said edge map that correspond to pixels in said ellipse pattern of said face template on said location on said edge map producing said best match metric, said coder being responsive to said control means for providing a higher detail level for said facial pixels. - View Dependent Claims (13, 14)
-
-
15. A method for detecting edge contours approximating a given feature in a pixel matrix representing a given image frame, said method comprising the steps of:
-
producing an edge map having a first plurality of edge pixels and a second plurality of non-edge pixels, each pixel in one of said first and second pluralities of pixels having an assigned value of +k and each pixel in the other one of said first and second pluralities of pixels having an assigned value of -k; defining a feature template having a feature pattern including a first and a second feature contour, said first and second feature contours being contiguous with each other and each of said feature contours having a plurality of pixels, each pixel in said first feature contour having an assigned value of -2k, each pixel in said second feature contour having an assigned value of +2k, and pixels in said feature template outside said first and second feature contours having an assigned value of 0k; and calculating sum-and-absolute-difference values between a block of pixels in said feature template and a corresponding block of pixels on said edge map corresponding to said block of pixels in said feature template at a given location of said feature template on said edge map, and using said sum-and-absolute-difference values to calculate an estimated correlation between edge contours on said edge map and feature contours in said feature template as a match metric. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23)
-
Specification