• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.663-670
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• 2019

The modified Canny edge detection algorithm that can detect the boundary between screen door and platform in the subway is proposed in this paper. Generally, in the subway, the boundary line between the platform and the screen door is darker than the surrounding area. Therefore, an edge image is using the modified bottom-hat transform by considering its characteristics. Double thresholded images with strong edge and weak edge through double thresholding are obtained. An algorithm that detects the boundary invasion between the platform and the screen door is proposed by calculating the length by applying the Hough transform to the double thresholded image and comparing the boundary line length between when there is an object such as a person and when there is no object. In this paper, the results of the proposed modified Canny edge detection algorithm using two different input images according to camera height position are shown by computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.946-950
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• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.521-525
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified removed.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.205-215
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• 2024

Manually mapping fractures in construction stone mines is challenging, time-consuming, and hazardous. In this method, there is no physical access to all points. In contrast, digital image processing offers a safe, cost-effective, and fast alternative, with the capability to map all joints. In this study, two methods of detecting the trace of discontinuities using image processing in construction stone mines are presented. To achieve this, we employ two modified Hough transform algorithms and the degree of neighborhood technique. Initially, we introduced a method for selecting the best edge detector and smoothing algorithms. Subsequently, the Canny detector and median smoother were identified as the most efficient tools. To trace discontinuities using the mentioned methods, common preprocessing steps were initially applied to the image. Following this, each of the two algorithms followed a distinct approach. The Hough transform algorithm was first applied to the image, and the traces were represented through line drawings. Subsequently, the Hough transform results were refined using fuzzy clustering and reduced clustering algorithms, along with a novel algorithm known as the farthest points' algorithm. Additionally, we developed another algorithm, the degree of neighborhood, tailored for detecting discontinuity traces in construction stones. After completing the common preprocessing steps, the thinning operation was performed on the target image, and the degree of neighborhood for lineament pixels was determined. Subsequently, short lines were removed, and the discontinuities were determined based on the degree of neighborhood. In the final step, we connected lines that were previously separated using the method to be described. The comparison of results demonstrates that image processing is a suitable tool for identifying rock mass discontinuity traces. Finally, a comparison of two images from different construction stone mines presented at the end of this study reveals that in images with fewer traces of discontinuities and a softer texture, both algorithms effectively detect the discontinuity traces.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.83-97
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• 1992

A new approach, to seam tracking for robotic are welding is proposed. In this approach, the weld model is a snapshot image and the acquired image is analyzed and compared to the welding database which contains CAD data, weld positions, weld parameters, etc. This paper presents a fast and robust algorithm for the Hough Transform. This modified Hough Transform(MHT) algorithm uses the least-squares regression analysis method in order to approximate the edge lines more precisely, and leads to a significant reduction in both computation and storage. In comparison with the conventional seam tracking methods, this new approach has the advantages of low cost, continuous welding, and various type welding.

• Journal of Biosystems Engineering
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• v.33 no.3
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• pp.196-203
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• 2008

Hybrid robust image processing algorithm to extract visual features of melon during the cultivation was developed based on a wireless tele-operative interface. Features of a melon such as size and shape including position were crucial to successful task automation and future development of cultivation data base. An algorithm was developed based on the concept of hybrid decision-making which shares a task between the computer and the operator utilizing man-computer interactive interface. A hybrid decision-making system was composed of three modules such as wireless image transmission, task specification and identification, and man-computer interface modules. Computing burden and the instability of the image processing results caused by the variation of illumination and the complexity of the environment caused by the irregular stem and shapes of leaves and shades were overcome using the proposed algorithm. With utilizing operator's teaching via LCD touch screen of the display monitor, the complexity and instability of the melon identification process has been avoided. Hough transform was modified for the image obtained from the locally specified window to extract the geometric shape and position of the melon. It took less than 200 milliseconds processing time.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.30-34
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• 2006

Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified Hough transform is used with clustering method for straight line detection. And the center points and diameters of inner and outer circle are found to determine eccentricity of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.263-279
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• 2009

Shape features in a content-based image retrieval (CBIR) system are divided into two classes: contour-based and region-based. Contour-based shape features are simple but they are not as efficient as region-based shape features. Most systems using the region-based shape feature have to extract the region firs t. The prior works on region-based systems still have shortcomings. They are complex to implement, particularly with respect to region extraction, and do not sufficiently use the spatial relationship between regions in the distance model In this paper, a region extraction method that is the combination of an edge-based method and a region growing method is proposed to accurately extract regions inside an object. Edges inside an object are accurately detected based on the Canny edge detector and the Hough transform. And the modified Integrated Region Matching (IRM) scheme which includes the adjacency relationship of regions is also proposed. It is used to compute the distance between images for the similarity search using shape features. The experimental results show the effectiveness of our region extraction method as well as the modified IRM. In comparison with other works, it is shown that the new region extraction method outperforms others.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.71-78
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• 2004

Real time and robust algorithm to extract the features of watermelon was developed from the remotely transmitted image of the watermelon. Features of the watermelon at the cultivation site such as size and shape including position are crucial to the successful tole-robotic operation and development of the cultivation data base. Algorithm was developed based on the concept of task sharing between the computer and the operator utilizing man-computer interface. Task sharing was performed based on the functional characteristics of human and computer. Identifying watermelon from the image transmitted from the cultivation site is very difficult because of the variable light condition and the complex image contents such as soil, mulching vinyl, straws on the ground, irregular leaves and stems. Utilizing operator's teaching through the touch screen mounted on the image monitor, the complex time consuming image processing process and instability of processing results in the watermelon identification has been avoided. Color and brightness characteristics were analyzed from the image area specified by the operator's teaching. Watermelon segmentation was performed using the brightness and color distribution of the specified imae processing area. Modified general Hough transform was developed to extract the shape, major and minor axes, and the position, of the watermelon. It took less than 100 msec of the image processing time, and was a lot faster than conventional approach. The proposed method showed the robustness and practicability in identifying watermelon from the wireless transmitted color image of the cultivation site.

• Journal of KIISE:Software and Applications
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• v.27 no.8
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• pp.846-854
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• 2000

In this paper, we propose effecient methods to extract the femoral head region in MR images. The femoral head area in MRI is approximated using Hough transform and the anatomical features of the femoral heads. Then, modified region growing method is applied to extract the femoral head region. We measured the parameters for the diagnosis of the avascular necrosis of the femoral heads from the segmented femoral head region. The proposed methods are proved very effective to extract the femoral head of healthy volunteer and of the patient having heavy avascular necrosis. The measured parameters can be used very efficiently for the quantitative analysis and the diagnosis of the avascular necrosis of the femoral heads.