To achieve full-surface strain measurement of variable curvature objects,a 360°3D digital image correlation(DIC)system is proposed.The measurement system consists of four double-camera systems,which capture the o...To achieve full-surface strain measurement of variable curvature objects,a 360°3D digital image correlation(DIC)system is proposed.The measurement system consists of four double-camera systems,which capture the object’s entire surface from multiple angles,enabling comprehensive full-surface measurement.To increase the stitching quality,a hierarchical coordinate matching method is proposed.Initially,a 3D rigid body calibration auxiliary block is employed to track motion trajectory,which enables preliminary matching of four 3D-DIC sub-systems.Subsequently,secondary precise matching is performed based on feature points on the test specimen’s surface.Through the hierarchical coordinate matching method,the local 3D coordinate systems of each double-camera system are unified into a global coordinate system,achieving 3D surface reconstruction of the variable curvature cylindrical shell,and error analysis is conducted on the results.Furthermore,axial compression buckling experiment is conducted to measure the displacement and strain fields on the cylindrical shell’s surface.The experimental results are compared with the finite element analysis,validating the accuracy and effectiveness of the proposed multi-camera 3D-DIC measuring system.展开更多
Hausdorff distance measure is one of the widely adopted feature-based image matching algo- rithms due to its simplicity and accuracy. However, it is considered that its robustness still needs to be improved. In this p...Hausdorff distance measure is one of the widely adopted feature-based image matching algo- rithms due to its simplicity and accuracy. However, it is considered that its robustness still needs to be improved. In this paper, various forms of original and improved Hausdorff distance （HD） and their limitations are studied. Focusing on robust Hausdorff distance （ RHD）, an improved RHD with an adaptive outlier point threshold selection method is proposed. Furthermore, another new form of the Hausdorff distance which possesses the merits of RHD and M-HD is prsented. Finally, a recur- sire algorithm is introduced to accelerate the image matching speed of Hausdorff algorithms. Exten- sive simulation and experiment results are presented to validate the feasibility of the proposed Haus- dorff distance algorithm.展开更多
The paper analyze and improve the SIFT optimized algorithm, and proposes an image matching method for SIFT algorithm based on quasi Euclidean distance and KD-tree. Experiments show that this algorithm has matching mor...The paper analyze and improve the SIFT optimized algorithm, and proposes an image matching method for SIFT algorithm based on quasi Euclidean distance and KD-tree. Experiments show that this algorithm has matching more points, high matching accuracy, no repealed points and higher advantage of matching efficiency based on keeping the basic characteristics of SIFT algorithm unchanged, and provides precise matching point to generate precise image stitching and other related fields of the follow-up product. At the same time, this method was applied to the layout optimization and achieved good results.展开更多
Feature-based image matching algorithms play an indispensable role in automatic target recognition （ATR）. In this work, a fast image matching algorithm （FIMA） is proposed which utilizes the geometry feature of ext...Feature-based image matching algorithms play an indispensable role in automatic target recognition （ATR）. In this work, a fast image matching algorithm （FIMA） is proposed which utilizes the geometry feature of extended centroid （EC） to build affine invariants. Based on at-fine invariants of the length ratio of two parallel line segments, FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features, and increases the feature diversity of different targets, thus reducing misjudgment rate during recognizing targets. However, it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation. An advanced FIMA is designed to cope with these problems. Experiments prove that the proposed algorithms have better robustness for Gaussian noise, gray-scale change, contrast change, illumination and small three-dimensional rotation. Compared with the latest fast image matching algorithms based on geometry features, FIMA reaches the speedup of approximate 1.75 times. Thus, FIMA would be more suitable for actual ATR applications.展开更多
A new fractal image compression algorithm based on high frequency energy (HFE) partitioning andmatched domain block searching is presented to code synthetic aperture radar (SAR) imagery. In the hybridcoding algorithm,...A new fractal image compression algorithm based on high frequency energy (HFE) partitioning andmatched domain block searching is presented to code synthetic aperture radar (SAR) imagery. In the hybridcoding algorithm, the original SAR image is decomposed to low frequency components and high frequencycomponents by wavelet transform (WT). Then the coder uses HFE of block to partition and searchthe matched domain block for each range block to code the low frequency components. For the high frequencycomponents, a modified embedded zero-tree wavelet coding algorithm is applied. Experiment resultsshow that the proposed coder obtains about 0. 3dB gain when compared to the traditional fractal coderbased on the quadtree partition. Moreover, the subjective visual quality of the reconstructed SAR imageof the proposed coder outperforms that of the traditional fractal coders in the same compression ratio(CR).展开更多
Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previou...Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.展开更多
Conventional correlation matching algorithms waste great time in invalid area search. This paper proposes a color tracking method based on correlation search area optimization on target characteristic hue decision. By...Conventional correlation matching algorithms waste great time in invalid area search. This paper proposes a color tracking method based on correlation search area optimization on target characteristic hue decision. By quantifying and reducing dimensions of HSV（ hue saturation value） color space, a one-dimensional hue space is constructed. In the space, the target characteristic hue granule set is constructed, which contains attributes such as value, area and average distance between pixels and aiming center. By using granular computing method, the similarity between target and search blocks is obtained and the invalid search areas can be removed. The color tracking experiment has proved that the algorithm can improve real time performance for conventional matching algorithms without precision lost.展开更多
A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin ar...A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.展开更多
trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalize...trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.展开更多
Aiming at the shortcoming that certain existing blockingmatching algorithrns, such as full search, three-step search, and dia- mond search algorithms, usually can not keep a good balance between high acoaracy and low ...Aiming at the shortcoming that certain existing blockingmatching algorithrns, such as full search, three-step search, and dia- mond search algorithms, usually can not keep a good balance between high acoaracy and low computational complexity, a block-maching motion estimation algorithm based on two-step search is proposed in this paper. According to the fact that the gray values of adjacent pixels will not vary fast, the algorithm employs an interlaced search pattem in the search window to estimate the motion vector of the objectblock. Simulation and actual experiments demanstrate that the proposed algmithm greatly outperforms the well-known three-step search and dianond search algoritlam, no matter the motion vector is large or small. Comparedc with the full search algorithm, the proposed one achieves similar peffomance but requires much less computation, therefore, the algorithm is well qualified for real-time video image processing.展开更多
A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generat...A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.展开更多
基金funded by the National Natural Science Foundations of China(Nos.12272176,U2037603).
文摘To achieve full-surface strain measurement of variable curvature objects,a 360°3D digital image correlation(DIC)system is proposed.The measurement system consists of four double-camera systems,which capture the object’s entire surface from multiple angles,enabling comprehensive full-surface measurement.To increase the stitching quality,a hierarchical coordinate matching method is proposed.Initially,a 3D rigid body calibration auxiliary block is employed to track motion trajectory,which enables preliminary matching of four 3D-DIC sub-systems.Subsequently,secondary precise matching is performed based on feature points on the test specimen’s surface.Through the hierarchical coordinate matching method,the local 3D coordinate systems of each double-camera system are unified into a global coordinate system,achieving 3D surface reconstruction of the variable curvature cylindrical shell,and error analysis is conducted on the results.Furthermore,axial compression buckling experiment is conducted to measure the displacement and strain fields on the cylindrical shell’s surface.The experimental results are compared with the finite element analysis,validating the accuracy and effectiveness of the proposed multi-camera 3D-DIC measuring system.
基金Supported by the National Natural Science Foundation of China(No.61072088)
文摘Hausdorff distance measure is one of the widely adopted feature-based image matching algo- rithms due to its simplicity and accuracy. However, it is considered that its robustness still needs to be improved. In this paper, various forms of original and improved Hausdorff distance （HD） and their limitations are studied. Focusing on robust Hausdorff distance （ RHD）, an improved RHD with an adaptive outlier point threshold selection method is proposed. Furthermore, another new form of the Hausdorff distance which possesses the merits of RHD and M-HD is prsented. Finally, a recur- sire algorithm is introduced to accelerate the image matching speed of Hausdorff algorithms. Exten- sive simulation and experiment results are presented to validate the feasibility of the proposed Haus- dorff distance algorithm.
文摘The paper analyze and improve the SIFT optimized algorithm, and proposes an image matching method for SIFT algorithm based on quasi Euclidean distance and KD-tree. Experiments show that this algorithm has matching more points, high matching accuracy, no repealed points and higher advantage of matching efficiency based on keeping the basic characteristics of SIFT algorithm unchanged, and provides precise matching point to generate precise image stitching and other related fields of the follow-up product. At the same time, this method was applied to the layout optimization and achieved good results.
基金Projects(2012AA010901,2012AA01A301)supported by National High Technology Research and Development Program of ChinaProjects(61272142,61103082,61003075,61170261,61103193)supported by the National Natural Science Foundation of ChinaProjects(B120601,CX2012A002)supported by Fund Sponsor Project of Excellent Postgraduate Student of NUDT,China
文摘Feature-based image matching algorithms play an indispensable role in automatic target recognition （ATR）. In this work, a fast image matching algorithm （FIMA） is proposed which utilizes the geometry feature of extended centroid （EC） to build affine invariants. Based on at-fine invariants of the length ratio of two parallel line segments, FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features, and increases the feature diversity of different targets, thus reducing misjudgment rate during recognizing targets. However, it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation. An advanced FIMA is designed to cope with these problems. Experiments prove that the proposed algorithms have better robustness for Gaussian noise, gray-scale change, contrast change, illumination and small three-dimensional rotation. Compared with the latest fast image matching algorithms based on geometry features, FIMA reaches the speedup of approximate 1.75 times. Thus, FIMA would be more suitable for actual ATR applications.
基金Supported by the National Natural Science Foundation of China (No. 90304003)the President Fund of GUCAS (No. O85101HM03).
文摘A new fractal image compression algorithm based on high frequency energy (HFE) partitioning andmatched domain block searching is presented to code synthetic aperture radar (SAR) imagery. In the hybridcoding algorithm, the original SAR image is decomposed to low frequency components and high frequencycomponents by wavelet transform (WT). Then the coder uses HFE of block to partition and searchthe matched domain block for each range block to code the low frequency components. For the high frequencycomponents, a modified embedded zero-tree wavelet coding algorithm is applied. Experiment resultsshow that the proposed coder obtains about 0. 3dB gain when compared to the traditional fractal coderbased on the quadtree partition. Moreover, the subjective visual quality of the reconstructed SAR imageof the proposed coder outperforms that of the traditional fractal coders in the same compression ratio(CR).
基金Supported by the Natural Science Foundation of China (50975133)the Innovative Foundation for Ph.D of the Jiangsu Province, China (2010-227)
文摘Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.
文摘Conventional correlation matching algorithms waste great time in invalid area search. This paper proposes a color tracking method based on correlation search area optimization on target characteristic hue decision. By quantifying and reducing dimensions of HSV（ hue saturation value） color space, a one-dimensional hue space is constructed. In the space, the target characteristic hue granule set is constructed, which contains attributes such as value, area and average distance between pixels and aiming center. By using granular computing method, the similarity between target and search blocks is obtained and the invalid search areas can be removed. The color tracking experiment has proved that the algorithm can improve real time performance for conventional matching algorithms without precision lost.
文摘A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.
基金Supported by the Natural Science Foundation of China(No.61311140262,61171163,61271021)
文摘trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.
基金supported by the Lab Open Fund of Beijing Microchemical Research Institute(P2008026EB)
文摘Aiming at the shortcoming that certain existing blockingmatching algorithrns, such as full search, three-step search, and dia- mond search algorithms, usually can not keep a good balance between high acoaracy and low computational complexity, a block-maching motion estimation algorithm based on two-step search is proposed in this paper. According to the fact that the gray values of adjacent pixels will not vary fast, the algorithm employs an interlaced search pattem in the search window to estimate the motion vector of the objectblock. Simulation and actual experiments demanstrate that the proposed algmithm greatly outperforms the well-known three-step search and dianond search algoritlam, no matter the motion vector is large or small. Comparedc with the full search algorithm, the proposed one achieves similar peffomance but requires much less computation, therefore, the algorithm is well qualified for real-time video image processing.
基金Supported by the National Natural Science Foundation of China (Nos. 40771176, 40721001)
文摘A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.
