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Published in:
2011 | OriginalPaper | Chapter
Local Binary Patterns, Haar Wavelet Features and Haralick Texture Features for Mammogram Image Classification Using Artificial Neural Networks
Authors : Simily Joseph, Kannan Balakrishnan
Published in: Advances in Computing and Information Technology
Publisher: Springer Berlin Heidelberg
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The objective of this study is the classification of mammogram images into benign and malignant using Artificial Neural Network. This framework is based on combining Local Binary Patterns, Haar Wavelet features and Haralick Texture features. The study shows the importance of Computer Aided Medical Diagnosis in successful decision making by calculating the likelihood of a disease. This multi feature approach for classification obtains an average classification accuracy of 98.6% for training, validation and testing.