• شماره ركورد
    44550
  • عنوان مقاله

    Proposed Classification System by Using Artificial Neural Network

  • پديد آورندگان

    mohammed, esraa z. ministry of communication - state company for internet services, iraq

  • از صفحه
    59
  • تا صفحه
    78
  • چكيده فارسي
    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.
  • كليدواژه
    GLCM , RLM , neural network , texture analysis
  • عنوان نشريه
    Kirkuk University Journal: Scientific Studies
  • عنوان نشريه
    Kirkuk University Journal: Scientific Studies