Machine learning apparatus and method for image searching

Computer image searching method for obtaining a desired image from a multiplicity of images, comprising the steps of:

• (a) providing a user-desired image subject to be recognized, the image subject being formed of a plurality of attributes;
• (b) using processor means, determining from the plurality of attributes, a subset of most discriminating attributes by:
• generating for each attribute a pair of histograms, the pair including a first histogram based on user input examples of the attribute and a second histogram based on user input counter examples of the attributes;
• generating weights and scoring functions of the attributes based on the histograms, including utilizing the pair of histograms generated for the attribute;
• and
• selecting scoring functions according to highest weight, the attributes corresponding to said selected scoring functions forming the subset of most discriminating attributes;
• (c) generating a functional template based on scoring functions for each discriminating attribute in the subset;
• and
• (d) using the functional template, matching a model of the desired image subject to images in the multiplicity of images, to extract those images having the desired image subject.

Computer image searching apparatus for obtaining a desired image from a multiplicity of images, comprising:

• input means for setting forth a user-desired image subject to be recognized, the image subject being formed of a plurality of attributes;
• processor means coupled to the input means for determining from the plurality of attributes a subset of most discriminating attributes, the processor means including:
• a histogram member coupled to the input means for generating a histogram for each attribute;
• processing means coupled to the histogram member for generating weights and scoring functions for the attributes;
• and
• a sorter for selecting scoring functions according to highest weight, the attributes corresponding to said selected scoring functions forming the subset of most discriminating attributes;
• wherein the processing means and sorter are coupled such that the processing means generates weights for each attribute, then the sorter selects attributes with the highest weights, and the processing means generates scoring functions for the selected attributes;
• a functional template member coupled to the processor means for providing a functional template based on scoring functions for each discriminating attribute in the subset;
• and
• an agent coupled to the functional template member to receive the functional template therefrom, the agent employing the functional template in a matching routine to extract images from the multiplicity of images, the extracted images having the desired image subject.

Computer image searching method for obtaining a desired image from a multiplicity of images, comprising the steps of:

• (a) providing a user-desired image subject to be recognized, the image subject being formed of a plurality of attributes;
• (b) using processor means, determining from the plurality of attributes, a subset of most discriminating attributes by:
• generating for each attribute a histogram;
• based on the histograms, generating weights for each attribute;
• selecting attributes with the highest weights;
• generating scoring functions for only the selected attributes;
• and
• selecting scoring functions according to highest weight, the attributes corresponding to said selected scoring functions forming the subset of most discriminating attributes;
• (c) generating a functional template based on scoring functions for each discriminating attribute in the subset;
• and
• (d) using the functional template, matching a model of the desired image subject to images in the multiplicity of images, to extract those images having the desired image subject.