Recognition System Of Green Pepper In The Field

The purpose of this research is to apply computer to automatically identify green peppers in the fields, and for realization of research about the fields picking green peppers robot in the future to lay the foundation. The main research content of this article as follows:1. Proposed segmentation method for the field peppers and leaves (branches) to using of the combination of color factors and histogram threshold.Through carefully statistics and analysis to color features of green peppers, leaves (branches) and so on among the peppers images taken in the field, proposed segmentation method about the combination color factor and histogram threshold of the peppers and leaves (branches) in the field.2. In order to accurately extract the shape characteristics of peppers image, in the paper, image pre-processing, such as image de-noising, binary morphology, edge detection and so on, are proposed. In the paper, use of median filtering to remove the image noise, because they will interfere to form a noise, reduce the image quality, when the image input or processing; The use of open and closed operations to process misjudge the regional in the image; Use Canny operator to process the image edge detection and to extraction feature of the target image contours.3. As a BP neural networks input, calculated and extracted green pepper characteristics of the five shapes, If the pretreatment peppers image directly as a neural network input then that will increase the amount of data, and slow identification rate. Therefore, extracted five normalized shape feature of pepper as a neural network input, including the form factor, stretch length, close degrees, aspect ratio, spindle circumference ratio.4. Construction BP neural network image recognition system. Through experiments, this paper identified the improved BP neural network model and the corresponding parameters. Including neural network layers, layers of nodes, activation function, learning rate, momentum factor and so on, and use a stable BP neural network to realize sample identification test. Finally, statistic and analysis recognition results.5. In this paper, using Least-squares method to fit the circle for extract the pepper centroid, and accurately locate pepper.