• Journal of IKEEE
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• v.22 no.4
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• pp.948-952
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• 2018

Haze removal is an object of scientific desire due to its various practical applications. Existing algorithms are founded upon histogram equalization, contrast maximization, or the growing trend of applying machine learning in image processing. Since machine learning-based algorithms solve problems based on the data, they usually perform better than those based on traditional image processing/computer vision techniques. However, to achieve such a high performance, one of the requisites is a large and reliable training database, which seems to be unattainable owing to the complexity of real hazy and haze-free images acquisition. As a result, researchers are currently using the synthetic database, obtained by introducing the synthetic haze drawn from the standard uniform distribution into the clear images. In this paper, we propose the enhanced equidistribution, improving upon our previous study on equidistribution, and use it to make a new database for training machine learning-based haze removal algorithms. A large number of experiments verify the effectiveness of our proposed methodology.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.399-408
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• 2012

Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from hand images. Many methods are available in scientific literature for fingertips detection with an open hand but very poor results are available for fingertips detection when the hand is closed. This paper presents a new method for the detection of fingertips in a closed hand using the corner detection method and an advanced edge detection algorithm. It is important to note that the skin color segmentation methodology did not work for fingertips detection in a closed hand. Thus the proposed method applied Gabor filter techniques for the detection of edges and then applied the corner detection algorithm for the detection of fingertips through the edges. To check the accuracy of the method, this method was tested on a vast number of images taken with a webcam. The method resulted in a higher accuracy rate of detections from the images. The method was further implemented on video for testing its validity on real time image capturing. These closed hand fingertips detection would help in controlling an electro-mechanical robotic hand via hand gesture in a natural way.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.383-389
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• 2016

In this paper, we present the hull blasting machine with vision-based weld bead recognition device for cleaning shipment exterior wall. The purpose of this study is to introduce the mechanism design of the high efficiency hull blasting machine using the vision system to recognize the weld bead. Therefore, we have developed a robot mechanism and drive controller system of the hull blasting robot. And hull blasting characteristics such as the climbing mechanism, vision system, remote controller and CAN have been discussed and compared with the experimental data. The hull blasting robots are able to remove rust or paint at anchor, so the re-docking is unnecessary. Therefore, this can save time and cost of undergoing re-docking process and build more vessels instead. The robot uses sensors to navigate safely around the hull and has a filter system to collect the fouling removed. We have completed a pilot test of the robot and demonstrated the drive control and CAN communication performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.453-458
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• 2016

One of the most common applications of machine vision is quality inspections in automated production. In this study, a welding inspection system that is controlled by a PC and a PLC equipped with a multi-camera setup was developed. The system was designed to measure the primary dimensions, such as the length and width of the welding areas. The TCP/IP protocols and multi-threading techniques were used for parallel control of the optical components and physical distribution. A coaxial light was used to maintain uniform lighting conditions and enhance the image quality of the weld areas. The core image processing system was established through a combination of various algorithms from the OpenCV library. The proposed vision inspection system was fully validated for an actual weld production line and was shown to satisfy the functional and performance requirements.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.366-371
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• 2014

This paper reports a machine learning approach for image object detection. Object detection and localization in a wild image, such as a STL-10 image dataset, is very difficult to implement using the traditional computer vision method. A convolutional neural network is a good approach for such wild image object detection. This paper presents an object detection application using a convolutional neural network with pretrained feature vector. This is a very simple and well organized hierarchical object abstraction model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.232-253
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• 1991

생산공정중에서 검사공정이 비교적 늦게 자동화되어 왔으나 Coordinate Measuring Machine(CMM)과 computer의 결합을 통하여 Computer-Aided Testing(CAT)이 실현되고 있다. 이 논문에서는 CAT에 대한 전반적인 개념을 설명하였으며, CAD 및 CAM과 CAT의 결합, expert system을 이용한 측정계획의 수립, vision을 이용한 측정자동화의 경향을 설명하고 있다. 또한 CAD와 Coordinate Measuring Machine(CMM)의 결합에 필요한 data교환 format을 소개한다. 그리고 현재 상용화 되어있는 CAT software들의 기능을 소개한다.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.67-74
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• 2001

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, quality and accuracy of PCB influence the performance of final product. It's attempted to obtain trust of 100% about all of parts. Because human inspection in mass-production manufacturing facilities are both time-consuming and very expensive, the automation of visual inspection has been attempted for many years. Thus, automatic visual inspection of PCB is required. In this paper, we used an algorithm which compares the reference PCB patterns and the input PCB patterns are separated an object and a scene by filtering and edge detection. And than compare two image using pattern matching algorithm. We suggest an defect inspection algorithm in PCB pattern, to be satisfied low cost, high speed, high performance and flexibility on the basis of $640{\times}480$ binary pattern.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.247-252
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• 2004

Developed shape awareness technology and vision technology for optical ten slant in this research and including external form state of lens for the performance verification developed so that can be good achieve badness finding. And, establish to existing reflex data because inputting surface badness degree of scratch's standard specification condition directly, and error designed to distinguish from product more than schedule error to badness product by normalcy product within schedule extent after calculate the error comparing actuality measurement reflex data md standard reflex data mutually. Developed system to smallest 1pixel unit though measuring is possible 1pixel as 3.7$\mu\textrm{m}$${\times}$3.7$\mu\textrm{m}$(0.1369${\times}$10/sub-1/$\textrm{mm}^2$) the accuracy to 10/sub-1/mm minutely measuring is possible performance verification and trust ability through an experiment prove.

• Journal of Chest Surgery
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• v.10 no.1
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• pp.143-147
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• 1977

Atrial septal defect is the most common of the congenital heart disease in the adult. Since the first description of atrial septal defect by Rokitansky in 1857, this anomaly has been studied by many workers in past one century. In 1953, Lewis had first corrected the atrial septal defect under direct vision with deep hypothermia, and Gibbon [1954] had first done the atrial septal defect under direct vision with extracorporeal circulation. In our college [May 2’ 1977], we have first repaired the A.S.D. under direct vision with artificial heart-lung machine and, the defect was 4x5cm in size which was closed by Dacron patch. This patient was 12 year old girl who is well now. [postoperative 13 days]

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.105-109
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• 2001

The micro optical parts such as ferrules are required to be manufactured within very small tolerances, as the slight deviation of the tolerance would give very large amount of loss in communication efficiency. For efficient optical communication, outer diameter, fiber diameter, fiber separation and eccentricity are significant parameters to be inspected., Thus we developed an automatic inspection system to evaluate shape parameters of the optical fiber connectors(ferrule) upto submicron accuracy using machine vision. new optical probe of multi fields of views has been developed and the image processing and data analysis algorithms have been complemented in real time basis. The developed system is successfully used in the practical ferrule manufacturing industry, and about 0.1$\mu\textrm{m}$ accuracy can be obtained with very fast inspection time.