Hoisting vertical rope is a continuum of one-dimensional movement during operation of hoist, and there are no appropriate ways to measure its vibration displacement at present. In this paper, a non-contact and unmarke...
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Hoisting vertical rope is a continuum of one-dimensional movement during operation of hoist, and there are no appropriate ways to measure its vibration displacement at present. In this paper, a non-contact and unmarked machine vision measurement method is proposed for measuring the transverse vibration displacement of hoisting vertical ropes. First, we construct the background image to extract the ropes by the background difference method. Subsequently, a novel row-column data statistics filtering algorithm is proposed and applied to the edgedetection image for removing the edges of the unmeasured rope. Finally, Hough transformation is used to locate the two edge lines at the boundary of rope and obtain the line parameters, which can be used to calculate the vibration displacement of the measured points at different times. The transverse vibration displacement of a moving hoisting vertical rope in a mine hoist was measured by using the reported machine vision measurement method, verifying the feasibility of the method. In order to verify the validity of the method, a simulation experimental system was built. The proposed method and the laser displacement sensor were used to measure the artificial transverse vibration displacement of a vertical rope simultaneously. The two results are in good consistency, which indicates that the proposed method can be fairly reasonable and accurate to measure the transverse vibration displacement of vertical rope in mine hoists.
The paper gives an overview of the algorithms developed to obtain reference lines and angles on X-ray images. These geometrical characteristics are used in the medical analysis of human joints. We propose the algorith...
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The paper gives an overview of the algorithms developed to obtain reference lines and angles on X-ray images. These geometrical characteristics are used in the medical analysis of human joints. We propose the algorithm's modifications based on the analysis of numerous X-ray images. These modifications allowed obtaining a great increase in calculation speed and the improvement of final results quality given by the corresponding application. They also lead to a significant reduction of manual tuning of the program, arising only in the rare cases when the properties of given images differ significantly from the mean ones.
This paper advances in a vision based driver assistance system for effective lane detection Technique. First method involves image processing technique initially to convert the Red, green and blue (RGB) into grayscale...
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ISBN:
(纸本)9781538695333
This paper advances in a vision based driver assistance system for effective lane detection Technique. First method involves image processing technique initially to convert the Red, green and blue (RGB) into grayscale images takes place by removing the effects of shades and immersion data of the images by maintaining the brightness of the images. Then to remove the sound available in the images and the obtained video is allowed to pass through the Gaussian filter in-order to remove sound from the images. The edges recognition is an important function to identify and detect the sharp break in an image by canny edge detection algorithm. Then Hough transform technique is applied to obtain the image pixels in the form of long straight line in the Hough space. So we can detect the lane if the vehicle tends to deviate from the lane in a complex situation and take corrective measures to change the lane.
Soybeans are an extremely important crop in the United States, providing the largest source of animal protein feed and a main source of vegetable oil in the country. The goal of this research is to identify methodolog...
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Soybeans are an extremely important crop in the United States, providing the largest source of animal protein feed and a main source of vegetable oil in the country. The goal of this research is to identify methodologies to estimate percent defoliation of the soybean canopy and leaves using RGB images taken in the field. The Mahalanobis distance classification method was used to process sets of images and calculate leaf area (number of pixels) corresponding to two classes (leaf and background) with eight different color groups. The canny edge detection algorithm provided an efficient method for detecting leaf edges, and threshold t(2) = 20 was found to be the optimal value for estimating soybean leaf edge. The segmentation results showed a performance of 96% for soybean leaves using Mahalanobis distance classification. Two statistical regression models (polynomial and logistic regression) for defoliation of soybean were developed based on individual images of trifoliate leaves taken from the field. The models both utilized leaf area and edge to provide estimates of soybean defoliation;however, a logistic equation has potential to provide greater understanding and more accurate estimates of defoliation with variations, especially at low defoliation. The R-2 and root mean square error (RMSE) of estimated and observed defoliation of trifoliate leaves were 0.90 and 6.16%, respectively. The validation of soybean canopy defoliation and its corresponding trifoliate leaves defoliation also provided reasonable correlation (R-2 = 0.96 and RMSE = 1.85%). This approach could lead to use of remotely sensed imagery for estimating defoliation in soybeans and timely intervention with integrated pest management strategies.
Iris plays a vital role in human life for object identification. Many models and techniques were proposed and suggested for detecting the Iris, but the accuracy was not achieved up to the level and its frequently used...
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Iris plays a vital role in human life for object identification. Many models and techniques were proposed and suggested for detecting the Iris, but the accuracy was not achieved up to the level and its frequently used for biometric application. The Proposed Work divided into two steps, at first, we detect the entire eye region outer layer by using mathematics first order derivatives by applying combinations of cannyedgedetection and circular hough transform. The next, we detect the inner portion of eye region that is Iris region is detected by combination of sobel edge detector and circular hough transform, As the results thereby reducing the error rate, marking the edges closest to the actual edges for maximizing the localization, indicating edges and also detect the inner and outer layer of the eye portions accurately. Finally this process is applied for cerebral palsy Children to detect the misalignment of eye and obtain the deviation position and results are compared with normal children eyes. In this context, image processing techniques are being recommended as a performance evaluation tool in cerebral palsy kids.
This study presents an approach to estimate the characteristics of multiple narrow-opening cracks from magnetic flux leakage (MFL) signals. The number, locations, orientations and lengths of the cracks are the objecti...
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This study presents an approach to estimate the characteristics of multiple narrow-opening cracks from magnetic flux leakage (MFL) signals. The number, locations, orientations and lengths of the cracks are the objective of the inversion process. The proposed procedure provides a reliable estimation of crack parameters in two separate consecutive steps. In the first step, the canny edge detection algorithm is used to estimate the number, locations, orientations and lengths of the cracks. Then, an inversion procedure based on space mapping is used in order to estimate the crack depths efficiently. The accuracy of the proposed algorithm is examined via simulations based on the finite element method as well as real experimental MFL data.
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