Image Feature Representation Using Code Vectors for Retrieval
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초록
The paper presents an algorithm which uses code vectors to represent corner geometry information for searching the similar images from a database. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. Taking the corner as the center coordinate, the angles of the intersecting lines are determined and are represented using code vectors. A code book has been used to code each corner geometry information and indexes to the code book are generated. For similarity measurement, the histogram of the code book indexes is used. This result in a significant small size feature matrix compared to the algorithms using color features. Experimental results show that use of code vectors is computationally efficient in similarity measurement and the corners being noise invariant produce good results in noisy environments.
Abstract
The paper presents an algorithm which uses code vectors to represent corner geometry information for searching the similar images from a database. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. Taking the corner as the center coordinate, the angles of the intersecting lines are determined and are represented using code vectors. A code book has been used to code each corner geometry information and indexes to the code book are generated. For similarity measurement, the histogram of the code book indexes is used. This result in a significant small size feature matrix compared to the algorithms using color features. Experimental results show that use of code vectors is computationally efficient in similarity measurement and the corners being noise invariant produce good results in noisy environments.
참고문헌 (21)
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