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
Z. Mohammed,E . "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
CHICAGO
E 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
VANCOUVER
Z. Mohammed E. Proposed Classification System by Using Artificial Neural Network. Kirkuk J. Sci.. 2015;10(3):59-78. doi: 10.32894/kujss.2015.104982