Abstract
Most of the existing local binary pattern methods discard local color differences by holding their binary information. And local spatial information is also neglected. To address these problems, a robust color image descriptor local color directional quaternionic pattern (LCDQP) is proposed. In the descriptor, the color distance map (CDM) is generated in the RGB color space to capture the color distribution among three channels. According to the distribution of CDM elements and their neighbors, four edge models are defined to describe the change trend of the original image. Then, based on this, the LCDQP strings are gained according to the distribution of four models in the four directions of 0 deg, 45 deg, 90 deg, and 135 deg. Finally, an effective quaternionic code method is adopted to construct the LCDQP descriptor. The proposed descriptor not only captures the local color features but also reflects the spatial structure information. Experiments on four representative databases demonstrate that the proposed descriptor is superior to other state-of-the-art approaches.
Highlights
Image descriptors are important in the fields of image processing, pattern recognition, and computer vision
In order to capture the cross-channel co-occurrence information and combine the color and spatial correlation information with the texture feature, we propose a simple and robust descriptor local color directional quaternionic pattern (LCDQP), by which four edge patterns for a color image are derived and the spatial distribution of patterns is considered
The indicator SðuÞ is replaced with a three-valued function and the binary local binary pattern (LBP) code is replaced by a ternary local ternary pattern (LTP) code, as shown in Eq (2)
Summary
Image descriptors are important in the fields of image processing, pattern recognition, and computer vision. The above discussed LBPs have proven to be highly discriminative features for texture classification and image feature description Because they threshold at exactly the value of the central pixel they tend to be sensitive to noise, in near-uniform image regions, and smooth weak illumination gradients. In order to capture the cross-channel co-occurrence information and combine the color and spatial correlation information with the texture feature, we propose a simple and robust descriptor local color directional quaternionic pattern (LCDQP), by which four edge patterns for a color image are derived and the spatial distribution of patterns is considered. According to the value difference between elements of CDM, four models are defined and their distribution of four directions is derived from CDM, which fully captures the edge and texture of local image region.
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