Fruit/Vegetable Recognition using OpenCV and Python
Object recognition is the process of finding a specific object in an image or video sequence. It has became an important application of image processing, and have attracted the attention of many programmers recently. Seng and Mirisaee indicates that fruit recognition can be applied for image retrieval, and educational purpose enhance learning, especially for small kids and Down syndromepatients, of fruits pattern recognition and fruits features classification based on the fruit recognition result. It can beused as a fruit recognition system in grocery store to automate labeling and computing the price. Our implementation included five steps: (1) Learning process.(2) Capture an image. (3) Compare between the captured image and images that had already been learnt using image histograms. Bradski and Kaehler indicates that histograms can be used to represent such diverse things as the color distribution of an object, an edge gradient template of an object, and the distribution of probabilities representing current hypothesis about an object’s location. They add, Histograms of edges, colors, corners, and so on form a general feature type that is passed to classifiers for object
recognition. (4) Find the image that matches the captured image.