Texture Classification using Angular and Radial Bins in Transformed Domain

نویسندگان

چکیده

Texture is generally recognized as fundamental to perceptions. There no precise definition or characterization available in practice. recognition has many applications areas such medical image analysis, remote sensing, and robotic vision. Various approaches statistical, structural, spectral have been suggested the literature. In this paper we propose a method for texture feature extraction. We transform into two-dimensional Discrete Cosine Transform (DCT) extract features using ring wedge bins DCT plane. These are based on properties coarseness, smoothness, graininess, directivity of pattern image. develop model classify images extracted features. use three classifiers: Decision Tree, Support Vector Machine (SVM), Logarithmic Regression (LR). To test our approach, Brodatz data set consisting 111 different patterns. Classification results accuracy F-score obtained from classifiers presented paper.

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ژورنال

عنوان ژورنال: International Journal of Advanced Computer Science and Applications

سال: 2021

ISSN: ['2158-107X', '2156-5570']

DOI: https://doi.org/10.14569/ijacsa.2021.0120301