Local Tetra-Directional Pattern–A New Texture Descriptor for Content-Based Image Retrieval

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Abstract
In this present work, a new technique for content-based image retrieval is introduced using local tetra-directional pattern. In conventional local binary pattern (LBP), each pixel of an image is changed into a specific binary pattern in accordance with their relationship with neighbouring pixels. Texture feature descriptor introduced in this work differs from local binary pattern as it exploits local intensity of pixels in four directions in the neighbourhood. Also, colour feature and gray level co-occurrence matrix have been applied in this work. Median of images have also been taken under consideration to keep the edge information preserved. The proposed technique has been validated experimentally by conducting experiments on two different sets of data, viz., Corel-1K and AT&T. Performance was measured using two well-known parameters, precision and recall, and further comparison was carried with some state-of-the-art local patterns. Comparison of results show substantial improvement in the proposed technique over existing methods.

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