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Classification by learning of wavelet and texture features

Publication Type : Book Chapter

Publisher : Springer

Source : Advances in Smart System Technologies, Advances in Intelligent Systems and Computing, Springer Singapore, pp 595 – 601, 2021.

Url : https://link.springer.com/chapter/10.1007/978-981-15-5029-4_49

Campus : Coimbatore

School : School of Engineering

Department : Computer Science and Engineering

Year : 2021

Abstract : Image classification is one among the significant tasks that can benefit industry through advancement in science and technology. Texture images possess a specific pattern that can be utilized to uniquely identify a texture class. Classification of Texture images can be done through proper selection of parameter that uniquely identifies an image in a group containing images of different classes. Machine learning approaches are currently the choice of implementation to provide accuracy and robustness in various fields like automatic image recognition, registration, and analysis. This work addresses machine learning methods to classify learnt texture samples through feature fusion of parameters obtained through wavelet and texture analysis.

Cite this Research Publication : Bagavathi C and Saraniya O, “Classification by learning of wavelet and texture features” in Advances in Smart System Technologies, Advances in Intelligent Systems and Computing, Springer Singapore, pp 595 – 601, 2021.

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