棉花中异性纤维检测图像分割和边缘检测方法研究进展

为进一步提高棉花中异性纤维的检测效率,对异性纤维图像处理方法进行探究。通过分析不同异性纤维图像边缘检测方法的定位精度、背景模糊以及受噪声影响情况发现,不同图像分割方法中异性纤维边缘连续性和分割效果存在差异性。统计了常见异性纤维图像边缘检测法和图像分割方法,分析了各类处理方法的优势和局限性,归纳了适用于各类异性纤维的检测方法,总结了现有研究中存在的问题和不足。研究认为:目前对不同种类异性纤维检测适用的图像处理方法不同,还无法同时检测出全部种类的异性纤维;应根据实践中具体异性纤维的种类、含量、物理特性等选择适合的检测算法并进行算法融合,开发普适性好的算法以降低成本和减少计算量。

Research progress in image segmentation and edge detection methods for alien fibers detection in cotton

In order to further improve the detection efficiency for picking up alien fibers among cotton, image processing methods for detecting alien fibers were reviewed. This paper analyzed the inaccurate location, background blur and the influence of noise in edge detection methods, and studied the edge continuity and segmentation effect of different alien fibers in the image segmentation methods. The common edge detection methods and image segmentation methods for alien fibers among cotton were discussed, advantages and limitations of various processing methods were analyzed, and the detection methods applicable to various alien fibers were summarized, pointing out the existing problems and deficiencies in current practice. It is concluded that different image processing methods are currently applied to detect different types of alien fibers, and it is not possible to detect all types of alien fibers at the same time. The paper highlighted that the suitable detection algorithms should be selected and combined according to the specific types, contents, physical characteristics of alien fibers to develop an universal algorithm in order to reduce the cost and calculation burden.