Papers by Keyword: Edge Detection

Abstract: This paper researched application of Canny algorithm on the color separation of golden image , to generate a separated golden image plate base on the extraction of golden area, so as to get the effect more closer to the real metallic. Canny algorithm is based on the gray-scale image segmentation algorithm. The image is mapped from RGB to Lab color space. According to the color attributes of b, the golden target regions are extracted using Canny algorithm. But it’s difficult to get the closed target boundary outlet by Canny algorithm, so this paper modified image segmentation algorithm. Firstly, the image is filtered by Canny operator; secondly, small areas on the Canny processed image are removed by using some pre-determined threshold value.; then processed the image through using smoothing and sharping method so to make inner area of image more smooth meanwhile improving boundary sharpness. The experimental results showed that the method based on Canny operator is very suitable for golden area extraction from a image. The golden target-regions can be closed boundary outlet, which makes the golden areas are more accurate and continuous.

Abstract: Image edge detection plays an important role in the process of image processing. This article classified the effect of various edge detection algorithms of digital images, mainly through the analysis of characteristics of the commonly used several kinds of classical edge detection operator in the time domain. For the actual image, the edge of the gray scale is sometimes not very clear, and the image also contains noise. A new algorithm of edge detection based on gray correlation degree and Kirsch operator is discussed in the paper. Kirsch operator is the reference sequence. Firstly, calculate the gray correlation degree of each pixel in the image and its neighbors formed eight action sequences and reference sequences, then determine the detection of edges based on gray correlation degree. The results show that this method can more accurately detect the useful information of the edge, and has a certain noise immunity. It is an effective and feasible new edge detection method.

Abstract: In this paper, we present a leaf vein extracting algorithm frame which deals with contour and interior vein by employing different methods. The interior vein extraction method based on gray scale processing, mathematical morphology and processing in details is presented. We apply gray-scale morphology to process the image and extract the vein information. Through the analysis of the image information, processing in details is adopted to clear the information on the other tissues and insignificant veins. The extracted significant interior vein is overlaid with the leaf contour extracted through edge detection by pixel union operation. Experiment results show the effectiveness of the proposed method.

Abstract: An edge detection method based on adaptive differential operator is proposed in this paper. Firstly, standard local edge models are built. And these edge models are described with four-bit-binary code (FBBC) which is obtained from weighted mean values in four directions. Then, based on weighted gray values in four directions, different differential operator templates are defined. And FBBC is used to build the matching between differential operator templates and edge models. Experiments show that this edge detection method with adaptive differential operator can smooth noise and has satisfactory edge detection result.

Abstract: Airport runway debris detection decides security of plane and passengers. The relative merits of the various types of sensor and the effects of adverse environmental conditions on their performance, a novel fuzzy weighted morphology algorithm of detection about runway debris is approved. The experimental results show that the proposed algorithm, compared with a few classic algorithms of edge detection, which can achieves the image edge precisely and reduce noises, better retain the image details, and adaptively detect the complete and successive edges.

Abstract: To successfully achieve high precision machining, process technology and on-machine measurement is essential. On-machine laser measurement will be widely used in industry because it is non-contacting, real-time and high-precision. However, proper method for tool shape monitoring and dimensional control are important to research. In this study, the measurement system consists of a laser light source and a quad photodiode array. And two different edge detection algorithms are introduced to determine the position of the tool edge accurately in order to measure the diameter of cutting tool and errors caused by tool runout. The experimental results verify the validity of measuring tool diameter and runout error.

Abstract: In order to solve the difficulty of low contrast feature extracting between labeled features and background, a new method combined the Hough transform and Canny algorithm is put forward for tensile test using the video extensometer, and a new algorithm edge detection is also obtained based on Canny an feature region tracking as well. The algorithm has proved to be a high positioning accuracy and computational efficiency in the test.

Abstract: In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional threshold’s shortage, a new wavelet packet transform adaptive threshold image de-noising method which is based on edge detection is proposed. By edge detection method, the wavelet packet coefficients corresponding to edge which is detected and other non-edge wavelet packet coefficients are treated by different threshold. Using the relativity among wavelet packet coefficients and neighbor dependency relation, at the same time, adopting the new variance neighbor estimate method and then the adaptive threshold is produced. From the experiment result, we see that compared with traditional methods, this method can not only effectively eliminate noise, but can also well keep original image’s information and the quality after image de-noising is very well.

Abstract: In order to improve the edge detection efficiency, and decrease the impulse noise impact on the edge detection, a new edge detection algorithm for impulse noise image is proposed. The algorithm combined the median filter idea, and used cross convolution template to calculate image gradients of horizontal and vertical direction. First, detected the point that will attend gradient calculation by threshold, for the noise point, its value will be replaced by median of those points associated with it in detection window. For non-noise point, we directly calculate gradient it initial pixel values. Experiments show that, the new algorithm has strong suppressing noise ability for images corrupted by impulse noise, the extracted image edge is also fine, the outline is clear, the algorithm is better than the traditional Sobel algorithm and the wavelet transform algorithm in noise suppression performance and the detection efficiency, it has strong practicability.

Abstract: Edge detection plays an important role in medical image processing; its accuracy directly affects the diagnosis and treatment of the disease. In view of the shortcomings of the traditional Sobel algorithm, an improved Sobel edge detection algorithm is proposed in this paper. Algorithm increased 135 º and 45 º direction templates, used the local gradient and standard deviation to filter and strengthen the gradient of initial gradient image. Experiments show that the image edge detected by the new algorithm is relatively accurate, complete and clear compared with the traditional Sobel algorithm, which verifies the effectiveness of the new algorithm.