Computer vision techniques become particularly important in agriculture applications due to their fast response, high accuracy and strong adaptability. Two of the most demanding and widely studied applications relate to object detection and classification. The task is challenging due to variations in product quality differences under certain complicate circumstances influenced by nature and human. Research in these fields has resulted in a wealth of processing and analysis methods. In this paper, we explicitly explore current advances in the field of object detecting and categorizing based on computer vision, and a comparison of these methods is given.