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Classification of CT Liver Images Using Local Binary Pattern with Legendre Moments


Affiliations
1 Mother Teresa Women's University, Kodaikanal, India
2 SRM University, Ramapuram, India
 

Liver cancer leads to more number of human deaths nowadays. Patient survival chances can be increased by early detection of the tumour. Texture analysis based on moment features for CT liver scan images is proposed here. The texture feature is extracted by local binary pattern and statistical features are extracted by Legendre moments. This communication presents a comparative analysis between these Legendre moments, local binary pattern and combined features. The classification accuracy of 96.17% is obtained for CT liver images. The experimental result shows that better texture classification is obtained using the proposed method.

Keywords

CT Liver Images, Feature Extraction, Legendre Moments, Local Binary Pattern.
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  • Classification of CT Liver Images Using Local Binary Pattern with Legendre Moments

Abstract Views: 421  |  PDF Views: 129

Authors

B. Vijayalakshmi
Mother Teresa Women's University, Kodaikanal, India
V. Subbiah Bharathi
SRM University, Ramapuram, India

Abstract


Liver cancer leads to more number of human deaths nowadays. Patient survival chances can be increased by early detection of the tumour. Texture analysis based on moment features for CT liver scan images is proposed here. The texture feature is extracted by local binary pattern and statistical features are extracted by Legendre moments. This communication presents a comparative analysis between these Legendre moments, local binary pattern and combined features. The classification accuracy of 96.17% is obtained for CT liver images. The experimental result shows that better texture classification is obtained using the proposed method.

Keywords


CT Liver Images, Feature Extraction, Legendre Moments, Local Binary Pattern.

References





DOI: https://doi.org/10.18520/cs%2Fv110%2Fi4%2F687-691