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Proposed Classification System by Using Artificial Neural Network | ||
| Kirkuk Journal of Science | ||
| Article 1, Volume 10, Issue 3, 2015, Pages 59-78 PDF (0 K) | ||
| DOI: 10.32894/kujss.2015.104982 | ||
| Author | ||
| Esraa Z. Mohammed | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| GLCM; RLM; neural network; texture analysis | ||
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