According to high precision of point cloud, countersink quality detection based on point cloud is an effective way to detect defect of countersink. One of the major processes in countersink quality detection is curved surface fitting. In this study, we eliminate point cloud interference considering curved surface which is not absolutely smooth and propose a curved surface fitting algorithm for building cone model by using circular curves and conical surfaces. The fitting algorithm is designed to establish model precisely considering diameter of edge, depth, and nest angel of countersink. In addition, to validate the performance of the algorithm, a computer vision approach which is developed in literature is presented and its results are compared with those obtained by using the fitting algorithm based on point cloud. Experimental results show that the fitting algorithm can be regard as an effective and precise algorithm for curved surface fitting under external interference in terms of experimental results. Furthermore, this study reveals that the proposed algorithm is more precision and has better anti-noise performance compared with computer vision detection approach. INDEX TERMS countersink, computer vision, curved surface fitting, feature extraction of point cloud, RANSAC.
Purpose The segmentation of printed circuit board (PCB) images is an important process in PCB inspection. The circuit traces, pads and vias in a PCB are dense and curved, and the PCB image obtained using different cameras or in different conditions may exhibit a large image gradient, which leads to inaccuracy and inefficiency in the PCB image segmentation. This paper aims to propose an improved local binary fitting level set method with prior graph cut, aiming to improve the accuracy and efficiency of the segmentation of PCB images obtained using different cameras or in different environments. Design/methodology/approach First, the paper constructs a 4-connected undirected graph using a given PCB image and classifies it based on the graph cut. Second, an adaptive initialization level set is implemented using the priori information obtained from the graph cut. Finally, the paper constructs a priori energy term using the prior information and introduces it into the energy function of the level set. Findings The approach results in an improved accuracy of segmentation in the context of a large gradient within the image. Experimental results demonstrate that the method can solve the deviation of artificially initialized level set from targets and improve the efficiency and accuracy of segmentation. Research limitations/implications This study only considers level set method as the research object. Iteration of the level set method takes a long time for a given huge PCB picture, which makes it impossible to apply to scenes with high real-time requirements. Practical implications PCB image segmentation is an important process in the PCB inspection. Since template matching and morphology techniques are well-established, image segmentation quality has a significant impact on the accuracy of detection. Originality/value This paper studies the segmentation of PCB images, improves the efficiency and accuracy of segmentation and facilitates the subsequent applications, such as in the nondestructive testing of PCB.
Based on the theory of gas molecular absorption spectrum, a transmission type gas cell based on cascaded GRIN lens has been designed. The gas cell is the kernel of the optical fiber gas sensor system. The system performance is relative to rationality of gas cell structure. By using GRIN lens couple in gas cell, we can solve the problems of optical discrete components. We use GRIN lens with pigtail fiber as collimating or focusing lens for transmission type of gas cell. To shorten sensor's size and length, and enhance sensor's sensitivity, we present a method by using cascaded GRIN Lens couples to compose a gas cell. With this method, the optical path length is increased and the detection sensitivity of the gas cell is greatly increased. This transmission type of gas cell based on cascaded GRIN lens couples have been applied to our system of absorption spectrum optical fiber gas sensors. We designed and manufactured a gas cell with cascaded GRIN lens couples. Experimental results show that transmission gas cell based on cascaded GRIN lens couples has a good detecting effect.
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