Image Retrieval Method Based on Improved Local Binary Pattern

Abstract

Local binary pattern (LBP) is an important image texture feature extraction method. This paper proposes a combination of adaptive threshold and directional local image feature representation, and to realize the image retrieval. This local combination feature is composed of two parts: 1)The standard deviation of the gray value of all pixels in the local neighborhood of the image and the gray value of the center pixel are used as the comparison threshold for encoding. This threshold is adaptively changed following the grayscale changes in the neighborhood, and can indicate the severity of the gray scale change; 2)directional local pattern: by comparing the grayscale changes of local neighborhood pixels in different directions, discrimination and binary encoding are performed to indicate the local texture features directionality. Finally, the two features are combined to form the local features of the image, and the features are used for image retrieval. Experiments on the Corel-1k database show that this method has a better image retrieval effect than existing local feature representation methods.