Differentiation of white blood cells from the microscopic im
The microscopic image is converted to grayscale image. The gray values are clustered by K-Mean clustering methods. The two binary images are generated for the nucleus region and cytoplasm region. These two images are used to extract the feature vector for the classification step. The pattern spectrum (pecstrum) is applied for the extraction of the feature set by the system. These extracted feature-sets of different types of white blood cells are collected and train the artificial neural network for the system. The system uses the trained ANN to classify the extracted feature vector and display the result.
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