ROBUST FEATURE IDENTIFICATION FOR IMAGE-BASED OBJECT RECOGNITION
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Accused Products
Abstract
Techniques are provided that include identifying robust features within a training image. Training features are generated by applying a feature detection algorithm to the training image, each training feature having a training feature location within the training image. At least a portion of the training image is transformed into a transformed image in accordance with a predefined image transformation. Transform features are generated by applying the feature detection algorithm to the transformed image, each transform feature having a transform feature location within the transformed image. The training feature locations of the training features are mapped to corresponding training feature transformed locations within the transformed image in accordance with the predefined image transformation, and a robust feature set is compiled by selecting robust features, wherein each robust feature represents a training feature having a training feature transformed location proximal to a transform feature location of one of the transform features.
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Citations
52 Claims
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1-31. -31. (canceled)
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32. An image feature detection device comprising:
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a tangible, non-transitory, computer-readable memory configured to store; robust feature detection software instructions including at least one implementation of a feature detection algorithm; and at least one medical training image; and at least one processor coupled with the memory and, upon execution of the robust feature detection software instructions, is configured to operate as a feature detector to; generate training features from the at least one medical training image according to the at least one implementation of the feature detection algorithm where each training feature has a corresponding training feature location within the at least one medical training image; transform at least a portion of the at least one medical training image according to an image transformation that includes at least a scale transform, thereby forming a transformed image portion; generate transform features from the transformed image portion according to the at least one implementation of the feature detection algorithm where each transform feature has a corresponding transform feature location within the transformed image portion; and store in the memory a set of robust features, wherein each robust feature in the set represents a training feature, based on the image transform, having a training feature transformed location proximal to a transform feature location. - View Dependent Claims (33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52)
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Specification