In the process of collecting hand vein images, due to the influence of image acquisition equipment, illumination and subcutaneous fat thickness, the contrast of hand vein images is relatively low. Meanwhile, vein extraction is seriously affected by image noise. To solve this problem, an algorithm of image segmentation and contrast enhancement based on features of venous gray value is proposed in this paper. Firstly, effective region of interest (ROI) is extracted and filtered through Wiener filtering. Secondly, a new image segmentation algorithm is obtained to extract vein image. The venous binary image is denoised by an 8-adjacent inner boundary tracking method and morphological processing. Finally, contrast-enhanced venous images are obtained by weight stack of the ROI and denoised images. The experiments results show that intravenous veins can be obtained perfectly by using the image segmentation algorithm based on features of venous gray value. Moreover, the high contrast venous images can be obtained.
Research on image segmentation algorithm based on features of venous gray value
First published at:Nov 30, 2018
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National Natural Science Foundation of China (61505192), Natural Science Foundation of Zhejiang Province (LQ15F050004)
Get Citation: Wang Dinghan, Feng Guilan, Wang Xiong, et al. Research on image segmentation algorithm based on features of venous gray value[J]. Opto-Electronic Engineering, 2018, 45(12): 180066.