The research presented in this paper was aimed to develop a recognition system for microscopic images of human tissues samples. The system should classify different types of tissues (i.e., Breast, Liver and blood cells). In this paper, co-occurrence matrix, run length matrix features combined with developed method to measure the roughness were used to extract a set of textural features in order to perform texture analysis for tissues samples. A feed forward neural network was used to classify different types of tissues according to the extracted feature vectors. For ANN training purpose the back-propagation training algorithm was used. Evaluation tests were carried on 550 tissues images. The test results indicated that the best attained success rate was around 93%. The proposed system was implemented using “visual basic.net” and all tests be done on windows operating system environment.
Z. Mohammed, E. (2015). Proposed Classification System by Using Artificial Neural Network. Kirkuk Journal of Science, 10(3), 59-78. doi: 10.32894/kujss.2015.104982
MLA
Esraa Z. Mohammed. "Proposed Classification System by Using Artificial Neural Network". Kirkuk Journal of Science, 10, 3, 2015, 59-78. doi: 10.32894/kujss.2015.104982
HARVARD
Z. Mohammed, E. (2015). 'Proposed Classification System by Using Artificial Neural Network', Kirkuk Journal of Science, 10(3), pp. 59-78. doi: 10.32894/kujss.2015.104982
VANCOUVER
Z. Mohammed, E. Proposed Classification System by Using Artificial Neural Network. Kirkuk Journal of Science, 2015; 10(3): 59-78. doi: 10.32894/kujss.2015.104982
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