An investigation of ramie fiber cross-section image analysis methodology based on edge-enhanced image fusion

Usually the quality of cross sectional fiber image is affected by the slicing and imaging device, some image processing techniques could be used to solve this problem instead of hardware operation. In this paper, a series of edge detection and weighted average image fusion algorithms are used to enhance the ramie fiber image to improve the quality of fiber cross-section image obtained by the traditional section and optical microscope. The cross-section characteristic parameters of ramie fiber could be extracted after the image pre-processing including threshold segmentation, median filtering and corrosion. The experimental results show that this method can be used to solve the identification problem of low contrast ramie fiber cross-section images caused by background blur, improve the accuracy of image recognition and analysis, it provides an effective algorithm basis for the digital measurement of ramie fibers.