Clinical Infrared Thermography is the best suited technique for early detection of breast cancer. Interpretation of breast thermographs helps in identifying the abnormality in the region. In recent years, computer Aided analysis of breast thermographs has been developed to interpret the abnormality. In general, the analysis involves decision making based on the features describing the abnormality. Various image analysis techniques are developed to extract the abnormality region and different statistical parameters are used for describing it. Artificial Neural Networks (ANNs) are used for classifying abnormality based on its severity. Potential research is carried out in this area of developing a generalized procedure for automatic analysis and classification of thermographs due to complex nature of the thermographs. This paper provides a detailed literature review on the various image analysis techniques, choice of statistical parameters and application of ANN for classification.