Research And Application Of Finish Image Based On NSCT

In the information age digital image is the one of the main and important ways to us to obtain the information. Researches on image processing technology and application are meaningful and valuable. And it's an important direction to the most of the domestic and international experts and research scholars.The NSCT is based on a nonsubsampled pyramid structure and nonsubsampled directional filter banks. It is a fully shift-invariant, multiscale, and multidirection expansion that has a fast implementation. The NSCT was proposed in 2005 and have been studied and used by many scholars, which has been quickly applied in image denoising, image enhancement and edge detection and so on, and good effect has been obtained. The research and experiment of the finish image processing technology have been made, the methods of the finish image processing is the key point, for the purpose of bottle automatic detection and the image processing key technologies involved are well studied.In the paper, first, the content and methods of image processing is simply introduced, with the focus on the feature extraction related theory, algorithm and technology, the research and experiment of the image processing based on wavelet transform and NSCT are mainly studies. After the research and experiment of the Gabor transform, the wavelet packet transform and NSCT, we obtain the numbers of the feature extraction and reach the purpose of the retrieval using NSCT. The new method is been obtained using the method of experimental NSCT grain image feature extraction for the purpose of the retrieval.To realize the automatic detection of the finish, the paper puts forward and tests the new methods to the finish image processing through the image segmentation,feature extraction,which can detect merit from demetirt, the finish image automatic testing function is realized using VC programming too. The scheme,first,detects the central position of the circle to the original image using Hough transform,then segments the bottle mouth image from the whole image according the inside and outside circle radius of the bottle mouth,and segments to several subimage with equal areas and equal direction. The characteristic value of each subimage is extracted using NSCT method,then the average value and variance of characteristic value is obtained to be the subimage feature vector,and nondestructive subimage feature vector is obtained to be the standard value,so the good or bad of the bottle mouth can be judged according the similarity of the subimage feature vector and standard feature vector. The experimental results show that this method is fast, has high detection accuracy and has good practical value.NSCT theory is more perfect, but its application of research is in the initial stage. So its development is bright and expected.