Abstract: [Objective] Aiming at fuzziness and noise of the vein image, we would like to propose a vein detection method for improving the anti-noise capability and detection effect by combining fuzzy logic and multiple order morphology.[Method] A square neighborhood with 5×5 pixels was built and each weight of the neighborhood pixel was set by the distance from it to the center pixel. A calculation method of pixel membership degree was proposed and then the vein image was transformed into fuzzy expression by using the triangle membership function. According to Sugeno fuzzy model and defined fuzzy rules, the vein image contrast was enhanced. The scales of two built square structuring elements were 3 and 5 respectively and the scales of four proposed linear structuring elements were 5. A determining method of the optimum linear structuring element was presented based on four convolution difference templates in different directions. Multiple percents were set. Then a multiple order morphology detection operator with multiple structuring elements and percents was proposed. Taking the vein images before and after adding noise for example, contrast experiments of eight different detection methods were done and peak signal to noise ratio was used to quantitatively evaluate the methods.[Result] The original image contrast was enhanced by 1.668 times and the maximum peak signal to noise ratio (52.624 6) could be got. The noise processing could be more effective and the extracted vein image was more clearer, complete and continuous than those of any other methods.[Conclusion] This method can effectively improve the anti-noise ability and vein detection effect, and is an effective means of detecting veins.

Key words: fuzzy logic, multiple order morphology, vein detection, noise restraining, structuring element