Histopathological Image Classification Using Efficient Bag-of-Features and Whale Optimization Algorithm

8 Pages Posted: 14 Jun 2019

See all articles by Varun Tiwari

Varun Tiwari

Rajasthan Technical University (RTU)

S C Jain

Rajasthan Technical University (RTU)

Date Written: March 20, 2019

Abstract

An automated digital histopathological image analysis is a complex procedure because of the accessibility of different morphological structures in the tissue images. For the equivalent, an efficient bag-of-features strategy has been proposed for histopathological image classification. Taken care bag-of- features method, the visual vocabulary is created by K-implies technique which indicates biasedness towards the at first chosen cluster heads. This paper proposed a whale optimization algorithm that utilizes bag of-features method. The proficiency of the proposed efficient bag-of- features whale optimization method has been tried on different standard benchmark functions. By combining both efficient bag-of-features based classification with whale optimization algorithm has been analyzed on blue histology image dataset and compared with different other meta-heuristic based bag-of-features methods. The explanatory result outcomes justify that the proposed technique outperforms the best in state-of-the-art strategy.

Suggested Citation

Tiwari, Varun and Jain, S C, Histopathological Image Classification Using Efficient Bag-of-Features and Whale Optimization Algorithm (March 20, 2019). Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur - India, February 26-28, 2019, Available at SSRN: https://ssrn.com/abstract=3356718 or http://dx.doi.org/10.2139/ssrn.3356718

Varun Tiwari (Contact Author)

Rajasthan Technical University (RTU) ( email )

India

S C Jain

Rajasthan Technical University (RTU) ( email )

India

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