Based On The Threshold Image Segmentation And Its Application In The Apple Positioning

Image segmentation is mainly interested in the specific area of extracted technology,it is the image recognition, image detection and image matching key step, from the image processing to the image analysis has played a pivotal role, occupied in the image is extremely Engineering important position.Threshold image segmentation is an important image segmentation technology, which is to select a desired segmentation threshold from histogram of the target image, and then according to the method of target image threshold segmentation.At first, this paper studied the global threshold segmentation algorithm,on the basis of basic segmentation algorithm based on the global threshold of the proposed two-dimensional histogram based multi-thresholding algorithm.Multi-threshold segmentation algorithm for low contrast image has better segmentation effect.For multi-threshold segmentation algorithm of high time complexity problem,using the improved genetic algorithm optimization algorithm split time.On the basis of the basic genetic algorithm to improve the population individual choices, make excellent directly into the evolutionary population, improved selection operator selection, mutation operator selection, improve the computational efficiency of genetic algorithm, so that the result of the convergence of the genetic algorithm is more accurate.Finally, the paper will be multi-threshold segmentation algorithm is applied to the apple tree red apple positioning.In order to ensure the integrity of the positioning of apple, and after multiple threshold algorithm segmentation of images for secondary processing, secondary treatment which includes images through a high threshold image segmentation low threshold image so that the target integrity better segmentation and mathematical morphology method to remove interference factor.Apple’s positioning rate can reach more than eighty percent, the effect is very ideal location.