Finger-vein identification has become the most popular biometric identify methods. The investigation on the identification algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein identification algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.
In this paper, a high-integration multi-spectral imaging lens was developed by micro-fabrication technology. By using multiple photo-etching and thermal reflow process, a microlens array and a multi-channels filter were integrated together without position mismatch. Besides, light block layer and isolation layer were brought in the structure to improve the imaging quality. Its fabrication process is described in detail and the optical property was tested by imaging experiments. The multi-spectral imaging lens has 9 optical channels, each channel capable of filtering and imaging independently. The imaging results indicate that the lens can capture pictures of visible bands and near-infrared band at the same time. Because of its high level of integration and image parallel capture capability, the novel lens is suitable to be applied in extracting conceal information and biomedical imaging.
Finger-vein recognition has became the most popular biometric identify methods. The investigation on the recognition algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein recognition algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.
Compound-eyes have several characters such as big vision field angle, small volume and multi-channels imaging. Therefore, it is applicable in the field of machine vision. Based on the thermal reflow and hot embossing technology, this paper put forward a new route to design the compound-eyes imaging system and analysis the optical aberration by use of ray tracing. Furthermore, in order to getting the optimal imaging ability, non-homogeneous micro-lens array is adopted as the compound-eyes structure. The ray-tracing results show that the design scheme can reach the expected requirements. Therefore, this paper can guide the design of compound-eyes imaging system.
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.
In this paper, we present a novel method of integrating a microlens array with a multi-channel filter based on Micro-Electro-Mechanical-System (MEMS) technique. The structure has several optical units and every unit can capture the information for a certain band. Therefore, it can be considered as a filtering artificial-compound-eye (ACE). By combining with a CMOS photo-detector, a multi-spectral imaging system was setup. The imaging experimental results prove that the structure can realize color separation and multi-units imaging as expected. Because of its compact structure and good optical property, the novel filtering ACE is suitable to be applied in smart multi-spectral imaging system.
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