The Research Of Automatic Recognition Of Cotton's Top

The production and development of Xijiang cotton have a great impact on Xinjiang economy and market stability of cotton in china. With the increase of cotton planting area, also Full mechanization of cotton production have become increasingly demanding, The key techniques on implementation the full mechanization of cotton production is cotton topping machine Highly control。Based on treatment technology of the pictures the topping recognition system of cotton pictures is regarded as an important part of cotton top cutting machinery Highly control, play an important role in the processing of cotton top cutting application。In this paper, based on cotton top cutting machinery working study on Automatic Identification System of topping image Identification used to cotton top-cutting machine. Provide theoretical and technical support for research top-cutting machine which achieve a high degree of automatic recognition of the cotton topping.This paper introduces the domestic and international image recognition research Situation, methods and the development direction, then we analyze and Process the cotton image combine with the Processing of grayscale, image denoising,, gray scale texture analysis, histogram statistics,, image feature extraction and image binarization. In order to carry out edge detection, In the course of image Preprocessing, the noise in images are removed by using the method of median filter and the method of edge-keeping filter. Then we sharpen the images with Laplace Operator. in order to facilitate the edge detection and image segmentation., Received good resultsat last Considering of the topping feature in the cotton image, we bring forward a recognition method of cotton topping image, a BP neutral network recognizer is devised. At the same time, we use VC++ as the develop language realize the relate algorithm during the image Preprocessing and cotton topping image recognition, Developed goal recognition software And the initial software testing and experiments, have been relatively satisfied with the results, indicating that the use of neural network technology to achieve the identification of cotton top is feasible, and the success rate of identification of the work to meet the basic needs of the software, For the future and lay a foundation for further study...