Method of recognizing images of faces or general images using fuzzy combination of multiple resolutions

A process for evaluating the similarity of a plurality of collections of images and for classifying the collections of images with respect to a known collection of images of objects of the same class, each of the collections containing only images of the same object produced at different orientations and resolutions, the resolutions being known for each image and being the same between the collections of images thereby forming sets of images at differing resolutions, the process comprising:

• (a) obtaining a plurality of different resolutions of an image to produce a collection of images to be classified;
• (b) providing a plurality of first modules implementing local autocorrelation coefficient feature extraction and providing a plurality of second modules implementing linear discriminant analysis and equal in number to the first modules, each of the first modules providing an output to each of the second modules to form pairs of modules, the second modules storing information characterizing a collection of known images of objects of the same class, the second modules providing information on similarity of images from the collection of images to be classified to the collection of known images, the pairs of local autocorrelation feature analysis modules and linear discriminant analysis modules operating only at resolutions of known and predetermined accuracy for both images of the collection of images to be classified and the collection of known images;
• (c) providing a third module for integrating outputs from the pairs of local autocorrelation feature extraction modules and linear discriminant analysis modules, and for merging information from the pairs of modules operating at multiple resolutions, the third module performing fuzzy integration;
• (d) training the third module, including measuring the performance of the pairs of local autocorrelation feature extraction modules and linear discriminant analysis modules to provide performance measurement;
• (e) combining the output of the pairs of local autocorrelation feature extraction modules and linear discriminant analysis modules based on the performance measurement;
• (f) producing an output similar to an output produced by one of the pairs of local autocorrelation coefficient feature extraction modules and linear discriminant analysis modules;
• and
• (g) providing a fourth module for analyzing the output from the third module such that recognition of images from the collection of images to be classified or rejection of the collection of images to be classified is effected relative to the images from the collection of known images, an output of the fourth module being an identification of each of the images from the collection of images to be classified as being similar to images from the collection of known images or as being different from the images in said collection of known images, wherein the pairs of local autocorrelation feature extraction modules and linear discriminant analysis modules in conjunction with the third module and the fourth module permit recognition or rejection of the images from the collection of images to be classified, the recognition or rejection being with respect to the collection of known images, the recognition or rejection having higher performance measurement than a performance measurement of any one of the pairs of local autocorrelation feature extraction modules and linear discriminant analysis modules in conjunction with one of the modules for implementing rejection or recognition.

A process for recognizing an unknown image with respect to sets of known stored images comprising:

• (a) obtaining a plurality of different resolutions of the unknown image;
• (b) performing location autocorrelation coefficient feature extraction followed by linear discriminant analysis for each resolution of the unknown image to produce a plurality of outputs;
• (c) combining the plurality of outputs into groups for each set of known stored images using fuzzy integration and producing a classifying number for each group;
• (d) performing recognition or acceptance of the unknown image by examining the classifying number and comparing the classifying number to a threshold;
• and
• (e) training the step of combining such that the plurality of outputs for the plurality of resolutions are combined in a manner other than averaging.