| Summary: | 碩士 === 國立清華大學 === 資訊工程學系 === 102 === We present a method to improve interest point descriptor on structure images that do not contain too many repeated patterns. In the proposed approach, interest point features are combined together based on shape context structure to maximize the feature descriptor capability based on extracted interest point information. The method involves constructing a shape structure for combining the geometry information into a single feature vector, generating histogram of the interest point distributions in the neighborhood, and incorporating the statistics information into the feature descriptor. At run time, features are transformed into a set of shape context to generate the feature descriptor. We apply the improved interest point descriptor to structure image matching and retrieval problems. Evaluation on a set of distortion images from a benchmark dataset shows that the proposed method outperforms the state-of-the-art feature descriptor methods. The proposed descriptor incorporates additional local geometry information with the shape context structure, and yields improvement in an image retrieval re-ranking system.
Additional Key Words and Phrases: Feature descriptor, structure image, shape context structure, image matching, and image retrieval re-ranking.
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