Papers by Keyword: Contour Extraction

Abstract: In this paper, frame differential method will be used to detect moving targets in a static background video file, and pre-contour can be obtained by binarizing the detected targets . However,, the result are not what was expected, so the expansion and corrosion of mathematical morphology are used to extract the final contour of moving targets. in the progress of dealing with massive data , mathematical morphology is not good enough to achieve the need of the real-time in video surveillance. Considering the dilation and erosion is a kind of parallel processing operations, in order to improve the speed of mathematical morphology operations, this paper offers detailed implementation process of the dilation algorithm for parallel computing on GPU. Experimental results showed that GPU parallel processing on mathematical morphology algorithm faster than the CPU serial processing.

Abstract: To remove the redundant points of image background in SFS reconstructed surface, a novel approach which combines the advantages of polygon scan and intersection algorithm and improves contour extraction method is proposed. In one hand, according to the gray scale level of pixels, the 3D profile of object is reconstructed by Shape from Shading method. In the other hand, firstly, the image is transformed into binary image through single-threshold segmentation method, the defects in image are remedied by morphological method, and the 2D contour of image is extracted through differential operator method; secondly, the image is divided into two parts using the polygon scan and intersection algorithm, that is the objective region and the background region; finally, the redundant points of image background in SFS reconstructed surface are removed through the fusing of 3D profile and 2D contour. Experiments shown that the proposed method can effectively remove the redundant points of SFS reconstructed surface, and it not only ensure the shape precision of SFS reconstructed surface, but also improve the universal of Shape from Shading technique.

Abstract: More and more applications of computer technology are used in the field of agriculture. In this paper, Image processing technology is applied to ginseng shape. Get a color image from the device, remove the color information and reserve the boundary information. Highlight the image edge information by gradient sharpening, binary image and use 8-neighbourhood algorithm for tracking the border.

Abstract: Contour curve is an important shape feature for vehicle recognition and it is a hard work to extraction it from complex dynamic traffic video for in-vehicle detection system. Snake Model is used to automatically extract the object contour curve proposed by Kass et al, but it is inability for traffic objects. Presented here is a novel approach for extracting vehicle contour curve by combining stereo vision with Snake Model. In this paper, Stereo vision is first used to segment vehicle from traffic background, then Snake Model is adopted to obtain complete contour curve. In view of classical Snake model is easily affected by noise, here we propose a improved Snake model by combining corner detection technology with Distance Potential Snake Model. Moreover, a vehicle identification method based on contour curve is presented. The method presented here was tested on complex traffic scenes and the corresponding results prove the efficiency of our proposed method.

Abstract: A method to extract contour of wheat pests based on LCV model is proposed in this paper. This method uses calculation of the weighted average gray value of the partial window function to replace the global mean value, and added the constraint level set function as a the energy term of signed distance function to avoid the re-initialization of the level set function. This method can be extracted the contour of wheat pests effectively, and thus it improves the efficiency of the extraction of wheat pests shape feature. The effectiveness of this method is verified by MATLAB simulation experiments.

Abstract: This paper researches on machine vision recognition and positioning technique which can help robot automatically recognize and accurately position smart meter in complex industrial environment. Firstly, crude position of the smart meter is obtained by recognition of liquid crystal display (LCD) screen through picture pre-processing. Secondly, the center positions of four screws are identified. Thirdly, the outline of the meter is calculated by geometric locations of the four screws, thus the meter is identified from the image and accurate position of the meter is calculated though the this paper’s algorithm. Experiments show that our algorithm can identify the meter rapidly and calculate the accurate position in complex environment, so the proposed algorithm is practical valuable.

Abstract: The simulation of the pattern has been an important part in embroidery, which can estimate the field of application of the stitches effectively and save the raw material before embroidery. This paper proposes a new simulated algorithm of contour extraction and image filled for embroidery patterns based on LOG(Laplace of Gaussian)operator. The experimental results show that the algorithm can achieve the expected effect.

Abstract: A yawning detection method which can be used in drivers’ fatigue monitoring is proposed. To adapt to the variance in different mouth shapes and sizes, it based on mouth inner contour corner detection and curve fitting. First, the Harris corner detection algorithm was used to detect inner mouth feature points. Second, we established the open mouths’ mathematical model by curve fitting those points, calculated the degree of mouth openness using the mouth model, and generated the real-time M-curve. Third, the duration of big openness in successive images is divided into levels for further judgment. The validation results show that the method can obtain more precise mouth parameters and distinguish yawn from complex mouth activities. So the method achieves a higher level of accuracy.

Abstract: The target contour extraction is one of key questions in computer vision. Because of its intrinsic limitations, the traditional C-V method can not meet the requirements of inclusion image contour extraction. To overcome this shortcoming, this paper introduces image overlay to make some improvements on the C-V methods, which is based on simplified Mumford-Shah, and compares the different contour extraction results caused by traditional method and improved C-V method. The results vindicate the efficiency and feasibility of improved C-V method.

Abstract: To improve the accuracy and efficiency of warp knitting CAD, a new approach to texture segmentation and contour extraction based on wavelet-transform, K-means clustering and Canny operator is proposed in this paper. The procedure is described as follows. Firstly the Daubechies wavelet and pyramid-structure is selected, then the approach decomposes the low frequency part of the fabric image. Secondly starting from the highest scaling level and considering all the four sub-bands, the image is automatic clustered and segmented by K-means clustering. During the process we should calculate the average mean and standard deviation of the three high-frequency coefficients at the current level and transform the higher scaling level label values to have the same mean and standard deviation. Lastly the texture’s contour of image is traced and extracted by Canny operator. The results show that this approach is a feasible way for jacquard fabric.