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Zhou L.-M.,National University of Defense Technology | Zhou L.-M.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | Zhang X.-H.,National University of Defense Technology | Zhang X.-H.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | And 2 more authors.
Zidonghua Xuebao/Acta Automatica Sinica | Year: 2015

There is a small size, lack of or less texture, transparent and reflective phenomenon on the images of convex objects. So the traditional reconstruction methods such as stereo-vision matching and active vision scanning such as laser or structure light cannot be used for such objects. In this paper, a reconstruction method based on multi-contours for miniature convex object is proposed. Firstly, multi-view silhouette images are captured, then the accurate contours are extracted; secondly coarse mesh is generated by space carving of multi-contours, and thirdly, the fragmented polygons are merged according to angle and area constriants; at last, the accurate mesh is generated by space carving of multi-polygons of the coarse mesh. The reconstruction experiments of regular and convex objects (syringe needle, diameter is about 3 mm) proved that the angular error is less than 0.7° and the time cost is less than 15 seconds and the total process is without manual intervention. This method can solve the problem of reconstruction and vision measurement of convex objects effectively. Copyright © 2015 Acta Automatica Sinica. All rights reserved. Source


Sun X.,National University of Defense Technology | Sun X.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | Long G.,National University of Defense Technology | Long G.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2015

This paper proposes a framework for small infrared target real-time visual enhancement. The framework is consisted of three parts: energy accumulation for small infrared target enhancement, noise suppression and weighted fusion. Dynamic programming based track-before-detection algorithm is adopted in the energy accumulation to detect the target accurately and enhance the target's intensity notably. In the noise suppression, the target region is weighted by a Gaussian mask according to the target's Gaussian shape. In order to fuse the processed target region and unprocessed background smoothly, the intensity in the target region is treated as weight in the fusion. Experiments on real small infrared target images indicate that the framework proposed in this paper can enhances the small infrared target markedly and improves the image's visual quality notably. The proposed framework outperforms tradition algorithms in enhancing the small infrared target, especially for image in which the target is hardly visible. © 2015 SPIE. Source


Liu H.,National University of Defense Technology | Liu H.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | Zhu Z.,Beijing Institute of Technology | Yao L.,National University of Defense Technology | And 9 more authors.
Optics and Lasers in Engineering | Year: 2016

3D metrology of a stereovision system requires epipolar rectification to be performed before dense stereo matching. In this study, we propose an epipolar rectification method for a stereovision system with two telecentric lens-based cameras. Given the orthographic projection matrices of each camera, the new projection matrices are computed by determining the new camera coordinates system in affine space and imposing some constraints on the intrinsic parameters. Then, the transformation that maps the old image planes on to the new image planes is achieved. Experiments are performed to validate the performance of the proposed rectification method. The test results show that the perpendicular distance and 3D reconstructed deviation obtained from the rectified images is not significantly higher than the corresponding values obtained from the original images. Considering the roughness of the extracted corner points and calibrated camera parameters, we can conclude that the proposed method can provide sufficiently accurate rectification results. © 2016 Elsevier Ltd. All rights reserved. Source


Sun X.,National University of Defense Technology | Sun X.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | Zhu Z.,National University of Defense Technology | Zhu Z.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | And 4 more authors.
Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology | Year: 2014

A saliency based heavy fixed pattern noise suppression algorithm for IR image which is captured by infrared focal-plane-array sensors in remote observation is proposed. The properties of the typical IR images characterized with small targets and heavy fixed pattern noise were analyzed, and it was found that the target regions are more salient than the background for observer in IR image. Using the saliency detection algorithm to detect target regions, the proposed algorithm processes different regions separately and suppresses the heavy fixed pattern noise effectively. Experiments indicate that our algorithm can detect the target regions accurately and suppress the heavy fixed pattern noise effectively. Source


Zhang Y.,National University of Defense Technology | Zhang Y.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | Zhou L.,National University of Defense Technology | Zhou L.,Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation | And 4 more authors.
Journal of Sensors | Year: 2016

In order to make the general user take vision tasks more flexibly and easily, this paper proposes a new solution for the problem of camera calibration from correspondences between model lines and their noisy image lines in multiple images. In the proposed method the common planar items in hand with the standard size and structure are utilized as the calibration objects. The proposed method consists of a closed-form solution based on homography optimization, followed by a nonlinear refinement based on the maximum likelihood approach. To automatically recover the camera parameters linearly, we present a robust homography optimization method based on the edge model by redesigning the classic 3D tracking approach. In the nonlinear refinement procedure, the uncertainty of the image line segment is encoded in the error model, taking the finite nature of the observations into account. By developing the new error model between the model line and image line segment, the problem of the camera calibration is expressed in the probabilistic formulation. Simulation data is used to compare this method with the widely used planar pattern based method. Actual image sequences are also utilized to demonstrate the effectiveness and flexibility of the proposed method. © 2016 Yueqiang Zhang et al. Source

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