In the healthcare domain, various techniques available for early disease diagnosis. Nail image analysis is one of the techniques for early stage disease diagnosis. Human fingernail image analysis is procedure consists of image capturing, pre-processing of image, image segmentation, segmentation of image, feature extraction. This paper presents review based generalized model for human fingernail image processing system, different classification techniques for nail feature classification and nail features. The nail features such as color, shape and texture used to predict diseases. Color features discussed are Mean, Standard Deviation, Skewness, Kurtosis and average RGB color. Shape features discussed in this paper are area, perimeter, roundness and compactness. Texture features are entropy, energy, homogeneity, contrast and correlation. Different classification techniques such as SVM classifier, KNN classifier, ANN classification used to classify the nail database for disease prediction are discussed.

image processing, feature extraction, disease detection, SVM, ANN, K-Nearest Neighbor, nail image analysis

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