Modeling Micro-Structure For Feature Extraction
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Abstract
Exemplary systems and methods use micro-structure modeling of an image for extracting image features. The micro-structure in an image is modeled as a Markov Random Field, and the model parameters are learned from training images. Micro-patterns adaptively designed from the modeled micro-structure capture spatial contexts of the image. In one implementation, a series of micro-patterns based on the modeled micro-structure can be automatically designed for each block of the image, providing improved feature extraction and recognition because of adaptability to various images, various pixel attributes, and various sites within an image.
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