Research And Implementation Of Forage Seed Microscopic Image Mosaicing System Based On Java Web

Image mosaic technology is a hot research topic in the field of computer vision, which is used to obtain panoramic images with high resolution and wide viewing angle by stitching together a plurality of overlapping images that associated with the same scene into seamless mosaic. Advantages of the technology are able to make the image acquisition device more economization and communization, and also make it easy to get wide and high resolution images.At present, most of the image mosaic systems that have been applied are console-based. This system’s development mode use the C/S mode, which can only for some more side wide and the user group does not have the network conditions. Therefore, its application is limited in a large scale. This system adopts B/S model development, extending the image matching system on the Internet. Users will be able to complete the image stitching work simply via browser rather than in the environment of MATLAB. The implementation of this system expand the using range of the image matching technology, and also make a meaningful exploration for the realization of the computer vision technology based on browser. The main work of this paper is as follows:First, this paper uses the J2EE architecture, SSH frame work to build forage image mosaicing system, which implements the function of the forage image mosaicing system. Secondly, using the traditional SIFT algorithm splicing image, image is easy to appear spell seams and pixel uneven transition, aiming at this problem, this paper proposes an adaptive Gamma correction method based on traditional SIFT algorithm. This method overcomes the disadvantages that exist seams in stitching results, eliminating the adverse effects caused by the illumination of image. Experimental results show this image stitching algorithm can get good fused image. Again, through the Java mixed with the MATLAB programming technology to realize image matching interface module. Realize the organic combination of algorithms and system. Finally, using the graphical user development environment GUIDE developed GUI interface of image matching algorithm, and converting the GUI file to an EXE executable file. This method solves the problem of MATLAB running environmental restrictions.