A new multi-level radial difference encoded pattern for image classification and retrieval
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A new multi-level radial difference encoded pattern for image classification and retrieval L. K. Pavithra1 · T. Sree Sharmila1 Received: 24 April 2019 / Revised: 15 February 2020 / Accepted: 24 February 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract An image can be represented by different types of feature descriptors. Each descriptor holds specific details about the image. The image classification and retrieval applications use these extracted features to classify the query image and retrieve similar kinds of images presented in huge databases for the given query image. The discriminant feature in the form of a binary pattern available around each pixel of the image is extracted by taking the local pixel difference between each pixel and its neighboring pixels (i.e., sampling points) present in different radii. The discrete wavelet representation (i.e., multi-resolution) of the image has more information about the image compared to the image present in the spatial domain since each level of the multi-level decomposition discloses significant details about the image in separate channels. However, binary pattern extraction around each coefficient of the different levels of decomposed images lacks in producing the discriminant texture feature representation since it extracts a feature from each decomposition level at a time and concatenates them. Thus, the proposed work extracts the binary pattern around each coefficient of different levels of decomposed image from different radii. Then, the obtained binary patterns available in different decomposition levels are encoded to represent the discriminant texture feature around each pixel location. Consequently, the proposed work selects the multi-level decomposition based on the stationary wavelet transform, since it has the same resolution in each level of decomposition. The performance of the proposed feature descriptor is assessed over seven different sets of databases using image classification and image retrieval applications. Finally, the performance of the proposed work is compared with the state-of-the-art techniques involved in extracting spatial arrangement details of pixels available in the image. Keywords Distance measure · Ensemble classification · Image retrieval · Multi-level decomposition · Radial difference binary pattern
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L. K. Pavithra [email protected] T. Sree Sharmila [email protected]
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Department of Information Technology, SSN College of Engineering, Kalavakkam, Chennai 603110, India
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Multidimensional Systems and Signal Processing
1 Introduction Every single image is created by arranging reflection coefficient of the captured natural scene or object in a specific way. In digital images, these reflection coefficients are called pixels. The structural arrangement of pixels reveals the degree of complexity present in an image. This pixel arrangement can be analyzed through extracting meaningful information such as color, texture, shape, and interest point details from them. Among the four mea
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