外文翻譯--基于批處理灰度圖像的拼接方法com組件技術(shù)

1、中文 中文 2110 字出處： 出處：Procedia-Social and Behavioral Sciences, 2013, 96: 2662-2666附錄 附錄 B 引用外文文獻(xiàn)及其譯文 引用外文文獻(xiàn)及其譯文COM component technology based batch gray images mosaic methodAbstractIn this paper, we present a gray image mos

2、aic component design method based on the vector rotating relax matching algorithm, which can handle batch images fast and with high quality. We compute the coordinate transformation matrix for full- scene image splicing

3、by using the image matching algorithm. The algorithm’s matrix operation implementation is based on the COM component technology toolbox in Matlab 7.0. We apply both fuzzy human visual restriction conditions for splicing

4、images and the multithread technology in the VC development environment to improve the matching algorithm performance efficiency. The experiment part demonstrates the execution efficiency of the proposed method, which s

5、hows that it can meet the real-time demand of the batch gray image mosaic software system.Keywords: image mosaic; image registration; relaxation matching.1. IntroductionFull scene image software based on image splicing a

6、ttracts great attention recently, such as Arc Soft Panorama Maker, Photoshop 8.0 etc. This software are often used to process image captured by the commercial camera or personal camera, which has high image quality. How

7、ever, that software is not suitable for the camera which is often used in high speed mode, complex and harsh shooting conditions, such as industrial cameras. The image quality and image fidelity captured by industrial

8、cameras are not as good as those captured by the personal camera or commercial camera, which more or less have different degrees of image distortion and reduce theaccuracy and stability of the automatic image mosaic algo

9、rithm(Liu, 2007).Because the main difficulty of image splicing lies on image registration, researchers put great attention on image registration technology in the past decades, and have achieved significant research re

10、sults (Kanazawa Miranda-Luna, Daul, Blondel, Hernandez-Mier, Wolf and Guillemin, 2008; Zitová (b) Software implementation of the image registration algorithmThe flowchart of the software for the image registration

11、 proposed in Sec. 2.1 is shown in Fig.1 (b). Fig.1 (b) shows that, the computation time of Step 1 and Step 2 can be overlap, and the corner points searching from the un-overlap area can be avoided based on the restrict

12、ion condition 1, which can improve the efficiency of the feature points searching algorithm, and the accuracy of the initial matching. Step 3 divides the corner point matrix got from Step 1 based on columns of the matr

13、ix. In this paper, we divide it into 4 blocks based on the height of the simulation image (1280×1024). All the corner point matrix blocks compute the grey similarity concurrently, and select the initial corner poin

14、t matching pairs based on the restriction condition 2. Step 6 clones the initial matching pair position coordinate set of the first image to be spliced got from Step 5 set into 4, and each set will be relax matching op