The feature extraction is the process to represent raw image in a reduced form to facilitate decision making such as pattern detection, classification or recognition. Finding and extracting reliable and discriminative features is always a crucial step to complete the task of image recognition and computer vision. Furthermore, as the number of application demands increase, an extended study and investigation in the feature extraction field becomes very important. The goal of this chapter is to present an intensive survey of existing literatures on feature extraction techniques over the last years. All these techniques and algorithms have their advantages and limitations. Thus, in this chapter analysis of various techniques and transformations, submitted earlier in literature, for extracting various features from images will be discussed. Additionally, future research directions in the feature extraction area are provided.