GLCM feature extraction for insect bites pattern recognition

Abstract

This paper describes the elements that are vital for feature extraction process from a Grey Level Co-occurrence Matrix. Every pattern recognition model consists of a primary phase where Feature Extraction is implemented, that focuses on determining distinct parameters from a given data. With respect to data set of images, which are a complex form of data, it is very difficult to analyze it’s features due to its nature. Image processing community is inundated with research on classification processes, none has been done on classification of insect bites ever before. This paper will propose a model to extract features from images of insect bites which can further be used so as to classify insect bites based on their vectors. Computer aided diagnosis can be achieved with successful detection of insect bites, that can aid at remote locations, such as Forests. Textural analysis of insect bite can help in classification of insect bites. The search for image point correspondences involves finding the interest points, neighborhood of those interest points are represented using vectors and finally the vectors are matched with the targeted image.