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Predictive model for skin disease in animals

Predictive model for skin disease in animals

There exists various experts system for skin disease diagnosis by using image processing. These models were implemented only for humans and plants skin disease detection. No model has been implemented for disease diagnosis among the animals. Different image segmentation algorithms are in place, which vary for different types of images like disease affected image, medical image etc. There are many classification techniques, algorithms and classifiers are available to distinguish the data into various classes. Each algorithm has their own benefits and drawbacks. Here the proposed system has been implemented by using image processing for skin disease detection in animals. In this approach, two common disease i.e. Alopecia, Ringworm has been taken. This proposed system used k-means clustering algorithm for image segmentation and SVM classifier to do classification of data in two different classes. Experiments are performed on available data to measure the accuracy and effectiveness of system. The proposed system also measures the execution time for each and every image of disease. This is investigated that which features have large impact on the developed methodology. Experimental results show the effectiveness of this model.

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