Papers by Keyword: Edge Detection

Abstract: The development of dry cell production in the world is advancing towards the high-speed and intellectualization direction, the input reduction for production cost by improving the comprehensive performance level and utilizing the advanced equipment has been the urgent demand for development of battery industry. The lagging situation that the detection by naked eye manually is relied to perform the quality assurance for dry cell substratum is broken based on the online high-speed automatic detection technology for pixel digitization of visual image. The principles on battery image processing and feature division as well as the principle on pixel over- fitting and accurate rectification during the process of pixel digitization detection for dry cell substratum are discussed in this paper, and such base and core for battery image processing as edge detection and accurate rectification technology are described.

Abstract: Images matching is the basis of image registration. For their difference, a improved SURF(speeded up robust features) algorithm was proposed for the infrared and visible images matching. Firstly, edges were extracted from the images to improve the similarity of infrared and visible images. Then SURF algorithm was used to detect interest points, and the dimension of the point descriptor was 64. Finally, found the matching points by Euclidean distance. Experimental results show that some invalid data points were eliminated.

Abstract: The edge detection is the important role in the image disposal. Traditional methods had some limitations more or less in practical applications such as pseudo-edge or need setting parameters by manual.Now, proposed a method can solve these problems in this paper. The histogram of gradient effective features was selected to composite the feature space, and during the process of classifier training, combined with AdaBoost and decision tree algorithm to improve the classification accuracy. Finally, the application of the algorithm proposed to image of Lena edge detection and comparative experimental show that the algorithm has better self-adaptability and good edge can be detected through this new algorithm.

Abstract: The support vector machine (SVM) has been shown to be an efficient approach for a variety of classification problems. It has also been widely used in target identification and tracking, motion analysis, image segmentation technology. Traditional detection methods mostly exist pseudo-edge and poor anti-noise capability. Under these circumstances, developing an efficient method is necessary. In this paper, we propose a new detection algorithm based on FSVM, the main idea is to train classified sample and give all training data a degree of membership, increase punishment to the wrong sub-sample. Then training and testing the FSVM classification model. Finally, extract edge of the image by using FSVM classification model. Experimental results show that the new algorithm can detect a clear image edge and have a good anti-noise nature.

Abstract: Based on digital camera method, there was using an improved dual-target method to measure atmospheric visibility. Using a digital camera to obtain images selected targets under different weather, to brightness contrast method and dual-target method were used to edge detection and Hough transform to obtain the image of the target and background, then respectively through the brightness contrast method and dual target method to calculate visibility value, in view of the different weather will dual target method and brightness contrast method and meteorological bureau issued the visibility value contrast experiment. Comparison results show that the digital camera method for visibility value and weather bureau data released by the trend is almost the same, especially dual target method. Digital camera method proved the effectiveness of Qingdao area visibility observation.

Abstract: Fast processing and recognition of image have an important influence on the real-time performance of AGV by vision navigation. The fast method of edge detection based on mathematical morphology for straight line path is proposed in this paper. Binary processing is implemented firstly for path image. Then the edge detection using morphological gradient can be executed directly, and image filtering and recognition of path edge can be realized simultaneously. Kinematics model of AGV is built and the shape of structure element in morphology processing can be adjusted in real time. The results of experiment show that recognition time of straight line path is shorten by this image processing method.

Abstract: An effective approach of quality inspection for micro hole is proposed by studying on the geometric feature of micro hole edge. The edge of micro hole is detected exactly with the digital image processing techniques, such as, the median filter, the threshold value transformation, and so on. The least square circle fit arithmetic and a new roundness measurement arithmetic are synthetically used in the processing of geometric feature recognition of micro hole. The practical results prove that the method with exact conclusion and high precision can satisfy the quality inspection requirement of micro hole.

Abstract: With the rapid development of computer science, image processing, and pattern recognition, people are paying more and more attention on research and application of machine vision, which has resulted in excellent results in many fields. Depending on the features of untouched, fast-speed, real-time, proper precision, anti-interference, the inspection technology based on machine vision has been researched deeply and comprehensive applied aboard. Recently, the size measurement technology based on machine vision has been applied in the size measurement of the machine processing parts. A case study of typical regular mechanical parts, algorithm of position and size measurement of line, circle center and radius are researched, and good results are got, which established an academic foundation for further measurement of complex parts.

Abstract: The accuracy of motion mechanism has been one of the most important factors which affect the precision of image acquired. In order to reduce its effect, we propose a novel method. We firstly get a frame acquired as reference image, under the condition that motion mechanism’s accuracy was given. Then gain corresponding parameter information through image analysis algorithms. Finally, motion mechanism makes corresponding adjustment according to analysis above. Experiments show that this method could acquire images more effectively.

Abstract: In practical problems, there are usually no clear counterparts as reference to evaluate restoration results. So no-reference blur assessment is very important and necessary. In this paper, we proposed an objective measure named as Edge Factor (EF) to appraise image blurring. The fundamental rationale was that blurring effect was much more perceptible in edge transition zones. The pixel number of edge transition zones would decrease when blurring occured. We defined the pixel number ratio of the edge transition zones to the whole image as EF. Experimental results show the monotonic consistency of EF and RMS. The proposed method is further compared with some common edge detection algorithms to demonstrate the effectiveness of combining point-based entropy with Pulse Coupled Neural Network.