Paper
18 November 2014 Enhancement display of veins distribution based on binocular vision and image fusion technology
Peng Liu, Si Di, Jian Jin, Liping Bai
Author Affiliations +
Abstract
The capture and display of veins distribution is an important issue for some applications, such as medical diagnosis and identification. Therefore, it has become a popular topic in the field of biomedical imaging. Usually, people capture the veins distribution by infrared imaging, but the display result is similar with that of a gray picture and the color and details of skin cannot be remained. To some degree, it is unreal for doctors. In this paper, we develop a binocular vision system to carry out the enhancement display of veins under the condition of keeping actual skin color. The binocular system is consisted of two adjacent cameras. A visible band filter and an infrared band filter are placed in front of the two lenses, respectively. Therefore, the pictures of visible band and infrared band can be captured simultaneously. After that, a new fusion process is applied to the two pictures, which related to histogram mapping, principal component analysis (PCA) and modified bilateral filter fusion. The final results show that both the veins distribution and the actual skin color of the back of the hand can be clearly displayed. Besides, correlation coefficient, average gradient and average distortion are selected as the parameters to evaluate the image quality. By comparing the parameters, it is evident that our novel fusion method is prior to some popular fusion methods such as Gauss filter fusion, Intensity-hue-saturation (HIS) fusion and bilateral filter fusion.
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Peng Liu, Si Di, Jian Jin, and Liping Bai "Enhancement display of veins distribution based on binocular vision and image fusion technology", Proc. SPIE 9268, Optics in Health Care and Biomedical Optics VI, 92681E (18 November 2014); https://doi.org/10.1117/12.2070929
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Cited by 1 scholarly publication.
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KEYWORDS
Image fusion

Image processing

Veins

Near infrared

Image enhancement

Image filtering

Principal component analysis

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