Local curve pattern for content-based image retrieval

Local binary pattern (LBP) is an effective image descriptor that is being used in various computer vision applications such as detection of faces, object classification, target detection, image retrieval etc., Since its success, different versions of LBP have been proposed to overcome its limitations. These techniques derive the pattern from the predefined set of image pixels which restrict the amount of information captured by them. In this work, a new approach is proposed in which the image pixels used to derive the pattern is selected based on the image characteristics. This technique uses image line/curve characteristics to derive the local pattern which we call it as local curve pattern. The line and curve characteristics are considered since they are the dominant components of an image and are used to represent the image effectively. The proposed method is evaluated using three different databases (viz Corel 1K, Corel 10K and Brodatz), and experimental result shows that the proposed method performs better than the conventional local pattern techniques.

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