Research On Infared Image Segmentation Algorithms Based On Fractionall Differential

The infrared image segmentation technology becomes increasingly thriving with the development of infrared technology, the infrared technology has already been used in every field from the last century, therefore the technology plays an important role in science and technology as well as the production and living, so the infrared image segmentation becomes a hotspot in the research of the everyone, then this article has carried out the study of the problem.The work of Image segmentation in this paper is mainly to dividing the image into a target region and background region, image segmentation is a basic and very important question in the field of computer vision, the stand or fall of segmentation result can cause the direct impact on the performance of the visual system. So whether it’s on the principle and application of it, or from the effect evaluation of application, in-depth study of image segmentation technology is of great significance.This article summarized all kinds of image segmentation algorithm and apply it to the infrared image segmentation, the method of infrared image processing experimental results are obtained. According to the characteristics of infrared image and infrared image segmentation research status, in this paper, fuzzy clustering infrared image segmentation algorithm is proposed based on fractional order differential and discussed the selection of fuzzy index m, using MATLAB simulation the segmentation algorithm is proposed in this paper, according to different values of m did a different experiment,through to compare the experimental results of algorithm in this paper and the experimental results of classic FCM algorithm, objectively prove the effectiveness of the algorithm. Based on this,maximum entropy threshold segmentation algorithm basedon fractional order differential is proposed, will all kinds of maximum entropy threshold segmentation and maximum entropy threshold segmentation based on fractional differential experiment contrast, once again proved that the infrared image segmentation based on fractional order differential is effective, at the same time, the threshold segmentation based on the fractional order differential and the fuzzy clustering segmentation based on the fractional order differential is compared, found that the effect of the fuzzy clustering segmentation based on fractional differential has the largely advantage than the maximum entropy threshold segmentation based on fractional differential, given a objective evaluation to the image segmentation algorithm in this paper from a perspective of the processing accuracy and efficiency of the algorithm, analyzed the advantages and disadvantages of each algorithm.