• 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:Software and Applications
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• v.31 no.6
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• pp.792-798
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• 2004

In this paper, we will introduce a new corner detector for the wafer die position recognition. The die position recognition procedure is necessary for WSCSP(Wafer Scale Chip Scale Packaging) technology, decide the accuracy of post-procedure. We present a hierarchical gray level corner detection method for the recognition of the die position from a wafer image. The new corner detector divides the corner region into many homocentric circles, and calculates the comer response and the angle of direction about each circle to get an accurate toner point. The new corner detector has a hierarchical structure so it can detect comer point more quickly than general gray level corner detector.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1278-1284
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• 2010

In this paper, we propose a new mura detection algorithm for TFT-LCD effectively, which is based on multi-point, 2-dimensional FFT. Since mura in TFT-LCD has a certain area shape, it is seen as a sin wave in a LCD line. Since shapes of mura can be seen a circle, horizontal oval, or vertical oval, it is shown that they can be detected by 2-dimensional FFT easily. Through simulation for test image, it is shown that proposed algorithm can detect various sizes of mura. The proposed algorithm can be utilized in automatic test equipment for effective TFT-LCD mura detection.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.398-405
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• 2018

In the HCI, hand gesture recognition is attracting attention as a method for interaction and information exchange between users and devices along with the development of IT devices. In hand gesture recognition through image processing, palm region detection is a key process contributing to improvement of processing speed and recognition rate. In this paper, we propose a new method for image segmentation between the hand and wrist for palm area detection. The anatomical characteristics of the hand are used to calculate the distance between the iliac bones of the thumb and little finger, which have the widest width, by the horizontal projection histogram of the hand image, and then the palm area is detected by drawing a circle having the width as the diameter. In order to verify the superiority of this method, multiple stage template matching is used to compare and evaluate recognition performance against the four conventional methods for 10 hand gestures. Note that the literatures to offer palm area detection performance evaluation are few although there are many studies on hand gesture recognition.

• Journal of Korean Neurosurgical Society
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• v.30 no.6
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• pp.711-716
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• 2001

Objectives : Three-dimensional computed tomographic angiography(3D-CTA) is recently developed diagnostic imaging modality. We have studied this noninvasive method for possible role in replacing conventional angiography( CA) in the detection of aneurysms of the circle of Willis in patients with subarachnoid hemorrahge(SAH). Methods : We studied retrospectively, the 100 patients with SAH or unruptured aneurysms admitted to our hospital from October 1997 to December 1998. Among there, 85 patients underwent CTA, 82 patients underwent CA and 67 patients underwent both of CTA and CA. 3D-CTA was obtained using maximum intensity projection(MIP) and shaded-surface display(SSD) reconstruction. Results : Total 107 aneurysms were detected in 92 patients, and 64 aneurysms were detected in 67 patients underwent both CTA and CA. In five cases of those 67 cases, aneurysms were detected by CA but not by 3D-CTA. The detection rate of aneurysms(91.8%) and the detection rate of parent artery in cases of anterior communicating artery aneurysms(86.9%) with total 3D-CTA were relatively compatible with that of CA. But 3D-CTA was not enough in detection of posterior communicating artery aneurysms, internal carotid artery aneurysms as well as small sized aneurysm(<3mm). Conclusion : We consider CTA is valuable in as a screening test for cerebral aneurysm and follow-up test. And it is also valuable in early surgery for patients with aneurysmal rebleeding because of simple, quick, non-invasive method.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.731-736
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• 2008

In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.97-106
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• 2010

In this paper, lane and curvature detection algorithm based on the curve template matching method is proposed. To eliminate the perspective effect of the original image, the input image is transformed to a top view image. From this top view image, its edge image is created. To increase the accuracy of detection, a novel edge detection method, which shows a strength in lane detection, is proposed. In the first step, straight lanes are detected from the edge image, and then the Curve Template Matching(CTM) method is applied to detect the curved lanes and to find their curvatures. Since the proposed CTM method uses only the simple equations, such as line and circle equations, to detect the curved lane, the algorithm is simple. Moreover, we used the detected lane information in the previous frames to detect the current frame's lanes, the detection results become more reliable. The proposed algorithm has been tested in various road conditions (highway, urban street, night time highway, etc.). Experimental results show that the proposed algorithm can process about 70 frames per second with the successful lane detection rate over 95% and curvature detection rate about 90%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1087-1104
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• 2015

An eye location based head posture recognition method is proposed in this paper. First, face is detected using skin color method, and eyebrow and eye areas are located based on gray gradient in face. Next, pupil circles are determined using edge detection circle method. Finally, head postures are recognized based on eye location information. The proposed method has high recognition precision and is robust for facial expressions and different head postures, and can be used in mouse operation. The experimental results reveal the validity of proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.36-37
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• 2014

기존에 영상 내에 원형 검출 방법으로 가장 널리 사용되는 방법은 허프 변환에 기초한다. 허프 변환은 해석적 곡선의 각 점을 원의 중심 좌표와 반지름으로 매핑 시키는 과정을 포함한다. 이러한 과정은 실행시간을 매우 많이 필요로 하고 또한 응용에 따라서 최적인 원 근사화 방법을 찾는데 문제점을 야기하기도 한다. 본 논문에서는 원형 모양인 광 연결 소자 장치로 제한된 응용환경에 대해 원 검출을 빠른 속도로 탐색하는 방법과 최적인 원 근사화 방법을 제안한다. 제안한 방법은 에지 검출과 검출된 에지를 이용한 중심좌표 및 반지름 탐색 그리고 최적화된 원 근사화 방법으로 구성된다. 모의실험을 통하여 제안한 방법은 기존의 오픈라이브러리로 제공되는 OpenCV의 허프 변환에 의한 방법에 비해 원 검출 및 근사화 방법에 있어 성능을 개선할 수 있음을 보인다.

• Journal of Korean Physical Therapy Science
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• v.6 no.4
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• pp.153-165
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• 1999

The transcranial Doppler(TCD) is a technique for measuring blood flow velocity of intracranial and extarcranial arteries. This examination based on Doppler effect which was first formulated in 1842 by the Austrian physicist Christian Doppler. In 1982, Rune Aaslid first maked 2MHz pulsed probe and recording intracranial vessels with transcranially. There are six criteria utilized in gaining positive identification of the intracranial vessels. The six criteria are as follows l)acoustical windows 2)depth of sample volume 3)direction of flow 4)spatial relationship of ACA and MCA bifurcation 5)mean velocity and 6)response common carotid artery compression and/or oscillation test. The affected factors for TCD examination are angle of insonation, posture of subject, age, gender, hematocrit, metabolic factors, and cardiac output. Clinical application of TCD are detection of stenosis, occlusion, emboli, thrombsis in intracranial and extracranial arteries and evaluation of cerebral arterovenous malformation, collateral capacity in the circle of Willis, ischemia cerebrovascular disease, stroke patient and vertebrobasilar system.