Image segmentation is an important step for finger-vein identification technique. However, it is difficult to extract precise details of the image because of the irregular noise and shades around the finger-vein. The repeated line tracking algorithm achieves good segmentation performance for low quality images of finger-vein, but it has some drawbacks such as low robustness and efficiency. In this paper, a modified repeated line tracking algorithm is proposed for image segmentation of finger-vein. Firstly, we propose a segmentation method called threshold image to execute rough segmentation and obtain binary and skeleton image of fingervein. Secondly, the width of finger-vein is estimated based on the binary and skeleton image. The parameters are revised according to the width. Then, the modified repeated line tracking algorithm is executed to figure out the locus space of finger-vein based on the revised parameters. Finally, processing results are obtained by using Otsu algorithm which executes exact segmentation on the locus space. Experiments show that the proposed algorithm is more robust and efficient than traditional repeated line tracking algorithm.

The replacement of humans by machines has gradually become a technological trend. In this study, a dual robotic arm was used in the belt conveyor operation system to track the screw and nut assembly using mutual visual tracking and positioning technology. Moreover, this study simulated the automatic assembly process using a dual robotic arm in a smart factory. An inverse kinematics operation was constructed using a geometric method to control the dual robotic arm to track the screw and nut assembly on the conveyor belt in real time using mutual visual tracking and positioning technology based on a single-lens charge-coupled device of a robotic arm. This study utilized a dual robotic arm to grab the screw and nut using fuzzy visual tracking control. After completing the grabbing of the screw and nut with tracking and positioning errors of 8%, the dual robotic arms continued to complete the assembly of the screw and nut. Therefore, through the establishment technology of mutual visual tracking and positioning of the dual robotic arm in this study, assembly tasks can be efficiently completed in related fields in the future.