Methods and apparatus for object recognition using textons

An apparatus for automatically recognizing objects in digital image data, comprising:

• an image processing control operably coupled to memory and functional processing units for controlling recognition processing, wherein the functional processing units comprise:
• an object detection unit for detecting an object of interest in input digital image data;
• a normalizing unit for obtaining a normalized object of interest;
• a texton generation unit for assigning texton representations of the normalized object of interest to produce a first texton array;
• and
• a similarity unit for determining a similarity between the texton representations and previously determined texton representations of at least one other object,
• wherein the detecting unit and normalizing unit detects and normalizes, respectively, a plurality of reference objects from a plurality of images, and further wherein the texton generation unit
• obtains a first plurality of filter responses based upon pixels forming the plurality of normalized reference objects,
• forms a first plurality of vectors based upon the first plurality of filter responses, and
• clusters the first plurality of vectors into a plurality of groups, wherein each group is assigned a texton label.

An apparatus for automatically recognizing objects in digital image data, comprising:

• an image processing control operably coupled to memory and functional processing units for controlling recognition processing, wherein the functional processing units comprise:
• an object detection unit for detecting an object of interest in input digital image data;
• a normalizing unit for obtaining a normalized object of interest;
• a texton generation unit for assigning texton representations of the normalized object of interest to produce a first texton array;
• and
• a similarity unit for determining a similarity between the texton representations and previously determined texton representations of at least one other object,
• wherein the similarity determination unit
• assigns texton labels to a probe image to produce a second texton array,
• determines first probabilities, for each location in the first and second texton arrays, that texton values of the normalized object of interest and the probe image are the same using the first conditional probability table,
• determines a probability of total similarity by multiplying all of the first probabilities;
• determines second probabilities, for each location in the first and second texton array, that texton values of the normalized object of interest and the probe image are different using the second conditional probability table,
• determines a probability of total dissimilarity by multiplying all of the second probabilities,
• computes a likelihood ratio using the probability of total similarity and probability of total dissimilarity, and
• determines a similarity between the normalized object of interest and the model image using the likelihood ratio.