Survey and comparison of different classification techniques for select appropriate classifier of image

Abstract

In human visual system, visual object classification is easy and effortless but in computer vision systems it is extremely hard Because of the various images of different objects within a specific class may have together with the various viewing conditions had led to have a serious problem. If some images have noisy contents or it contains blurry data, thus it is very hard to classify these types of images. Images processing introduces several techniques which be able to classify the data, but if image is blurry or noisy so they can not able to give the acceptable results. In this survey discuss the main classification methods consider, Supervised learning and unsupervised learning. The major motivation of this survey is to gives a brief comparison among different images classification techniques and methods. Finally, it is determined method that more accurately   if an image contains blurry or noisy data.