Papers by Keyword: Image Edge Detection

Abstract: Micro-structure dimension metrology is a grand challenge to current metrological methods and tools. In this paper, a retraceable metrological scanning electron microscopy (M-SEM) system with precision stage and laser interferometer is presented in detail. The double stages structure is used to realize both sample positioning in 50mm×50mm range and accuracy imaging in several tens of micron scale. In order to acquiring metrological scanning image, the control system based on digital signal processing (DSP) is constructed. Furthermore, this paper focuses on demonstrating a metrological SEM image edge detection algorithm which is the essential part of the metrological SEM system to realize the traceable metrology of line width.

Abstract: With mobile platform development there are more and more Android-based image processing applications. The principles of four kinds of edge detection algorithms are analyzed in this paper and such algorithms are realized by adopting JNI technology based on android platform. At last the effect and efficiency of such algorithms are also compared and summarized.

Abstract: Cells are fundamental units of life, and the key point in the field of biomaterial. Biological cells are always with high density, small nucleus and much impurities. Based on the technology of image processing, we propose a new method to count cells on the image of microscopic cells with high level of recognition. To precisely count the number, our method includes edge detecting and marking, efficient usage of three channel information of enhanced nucleus, binaryzation of dynamic threshold in separated areas and finally denoising. The experiment shows that the method is precise and quickly-reacted, moreover it can effectively rule out the impact of impurities. With little adjustment, it can apply to some other fields, not only decrease the labor involved, but the budget as well.

Abstract: The tongue diagnosis is an important diagnostic method in Traditional Chinese Medicine (TCM). Human tongue is one of the im­portant organs which contain the information of health status. Image segmentation has always been a fundamental problem and complex task in the field of image processing and computer vision. Its goal is to change the representation of an image into something that is more meaningful and easier to analyze. In other words, it is used to partition a given image into several parts in each of which the intensity is homogeneous. In order to achieve an automatic tongue diagnostic system, an effective segmentation me­thod for detecting the edge of tongue is very important. We mainly compare the Chan Vese Method and Canny algorithm for edge segmentation. The segmentation using Canny algorithm may produce many false edges after cutting; thus, it is not suitable for use. But, for our two steps Chan Vese method can automatically select the best edge information. Therefore, it may be useful in clinical automated tongue diagnosis system. Experiments show the results of these techniques.

Abstract: Digital image processing technology is widely used in the further application of computer graphics. This thesis introduces a digital image processing teaching demonstration system including image file management, image transformation, color image processing, binarization, image enhancement, and image edge detection extra. In function, it embraces basic skills in digital image processing. This thesis is a favorable assistant in your study and practical application by means of friendly operation interface, the contrast of image processing effect demonstration and algorithm routine.

Abstract: This paper presents a neural network adaptive image edge detection method, and from neural network theory, this paper gives the formula of adaptive neural network algorithm; quantitative given the momentum factor and error, momentum factor and error on the weight vector of norm of the gradient of the quantitative relationship; and gives the algorithm flow diagram. Through experiment we get the conclusion: by using this adaptive neural network for image edge detection is feasible, and it has good generalization ability.

Abstract: Comparing with the phytoplankton, there are few researches on zooplanktons. Now, many waterworks don’t monitor the zooplanktons in source water. There isn’t effective detection method for several common macro zooplanktons such as chironomid larvae, cyclops and so on, and little has been done in the field of the macro zooplanktons automatic identification and monitor. This paper puts for forward a macrozooplankton edge detection method based on wavelet packet decomposition and reconstruction. We erase the high frequency parts by applying wavelet packet decomposition in the original images and then detect the edge of reconstruction images using the common edge detectors such as Prewitt, Sobel, Roberts, Laplacian of Gaussion, Canny and so on. The experimental results show that the edge detection methods in the reconstruction image work better than in the original image.