A novel technique for calibrating crucial parameters of chassis components is proposed,which utilizes the machine vision metrology to measure 3D coordinates of the center of a component's hole for assembling in th...A novel technique for calibrating crucial parameters of chassis components is proposed,which utilizes the machine vision metrology to measure 3D coordinates of the center of a component's hole for assembling in the 3D world coordinate system.In the measurement,encoding marks with special patterns will be assembled on the chassis component associated with cross drone and staff gauge located near the chassis.The geometry and coordinates of the cross drone consist of two planes orthogonal to each other and the staff gauge is in 3D space with high precision.A few images are taken by a highresolution camera in different orientations and perspectives.The 3D coordinates of 5 key points on the encoding marks will be calculated by the machine vision technique and those of the center of the holes to be calibrated will be calculated by the deduced algorithm in this paper.Experimental results show that the algorithm and the technique can satisfy the precision requirement when the components are assembled,and the average measurement precision provided by the algorithm is 0.0174 mm.展开更多
Image entropy and empirical mode decomposition （EMD） are effective methods for target detection. EMD algorithm is a powerful tool for adaptive multiscale analysis of nonstationary signals. A new technique based on E...Image entropy and empirical mode decomposition （EMD） are effective methods for target detection. EMD algorithm is a powerful tool for adaptive multiscale analysis of nonstationary signals. A new technique based on EMD and modified local entropy is proposed in small target detection under sea-sky background. With the EMD algorithm, it is valid to estimate the background and get the target image by removing the background from the original image and segmenting the target based on the modified local entropy method. The data analysis and experiments show the validity of the proposed algorithm.展开更多
We propose an improved algorithm based on fractal dimension and third-order characterization to detect dim target with cluttered background in an infrared （IR） image. We also illustrate the performance and efficienc...We propose an improved algorithm based on fractal dimension and third-order characterization to detect dim target with cluttered background in an infrared （IR） image. We also illustrate the performance and efficiency comparisons between the presented algorithm and the traditional fractal detection method on real IR images. The experimental results show that the proposed algorithm is robust and efficient for IR dim target detection.展开更多
基金supported by the National Natural Science Foundation of China (Nos.60808020 and 61078041)the Tianjin Research Program of Application Foundation and Advanced Technology (No.10JCYBJC07200)
文摘A novel technique for calibrating crucial parameters of chassis components is proposed,which utilizes the machine vision metrology to measure 3D coordinates of the center of a component's hole for assembling in the 3D world coordinate system.In the measurement,encoding marks with special patterns will be assembled on the chassis component associated with cross drone and staff gauge located near the chassis.The geometry and coordinates of the cross drone consist of two planes orthogonal to each other and the staff gauge is in 3D space with high precision.A few images are taken by a highresolution camera in different orientations and perspectives.The 3D coordinates of 5 key points on the encoding marks will be calculated by the machine vision technique and those of the center of the holes to be calibrated will be calculated by the deduced algorithm in this paper.Experimental results show that the algorithm and the technique can satisfy the precision requirement when the components are assembled,and the average measurement precision provided by the algorithm is 0.0174 mm.
基金supported in part by the National Natural Science Foundation of China for Young Scholars under Grant No.40801164
文摘Image entropy and empirical mode decomposition （EMD） are effective methods for target detection. EMD algorithm is a powerful tool for adaptive multiscale analysis of nonstationary signals. A new technique based on EMD and modified local entropy is proposed in small target detection under sea-sky background. With the EMD algorithm, it is valid to estimate the background and get the target image by removing the background from the original image and segmenting the target based on the modified local entropy method. The data analysis and experiments show the validity of the proposed algorithm.
文摘We propose an improved algorithm based on fractal dimension and third-order characterization to detect dim target with cluttered background in an infrared （IR） image. We also illustrate the performance and efficiency comparisons between the presented algorithm and the traditional fractal detection method on real IR images. The experimental results show that the proposed algorithm is robust and efficient for IR dim target detection.
