• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.550-555
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• 1993

The aim of this paper is to present the development of visual seam tracking system equipped with visual range finder. The visual range finder, which consists of a CCD camera and a diode laser system with line generating optics, developed to recognize the types of weld joints and detect the location of weld joints. In practical applications, however, images of the weld joints are often degraded due to spatters, are flares, surface specularity, and welding smoke. To overcome the problem, this paper proposes a syntactic approach which is a class of artificial intelligence techniques. In the approach, the type of weld joint is inferred based upon the production rules which are linguiques grammars consisting of a set of line and junction primitives of laser strip image projected on weld joint. The production rules eliminate several noisy primitives to create new primitives through the merging process of primitives. After the recognition of weld joint, arc welding is started and the location of weld joints is repeatedly detected using a spring model-based template matching in which the template model is a by-product of the recognition process of weld joint. To show the effectiveness of the proposed approach a series of experiments-identification and robotic tracking-are conducted for four different types of weld joints.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1123-1127
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• 2005

The Conventional methods of color separation in computer-based machine vision offer only weak performance because of environmental factors such as light source, camera sensitivity, and others. In this paper, we propose an improved color separation method using RGB, HLS, color coordination space, and fuzzy similarity measure. RGB consists of red, green and blue, the three primary colors of light. HLS includes hue, light and saturation, the human recognition elements of co]or. A fuzzy similarity measure was employed for evaluate the similarity among fuzzy colors with the six features of RGB and HLS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2415-2423
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• 1999

We propose a new optical method which conceals the data of authorized persons by encryption before they are stored or compared in the pattern recognition system for security systems. This proposed security system is made up of two subsystems : a proposed optical encryption system and a pattern recognition system based on the JTC which has been shown to perform well. In this system, each image of authorized persons as a reference image is stored in memory units through the proposed encryption system. And if a fingerprint image is placed in the input plane of this security system for access to a restricted area, the image is encoded by the encryption system then compared with the encrypted reference image. Therefore because the captured input image and the reference data are encrypted, it is difficult to decrypt the image if one does not know the encryption key bit stream. The basic idea is that the input image is encrypted by performing optical XOR operations with the key bit stream that is generated by digital encryption algorithms. The optical XOR operations between the key bit stream and the input image are performed by the polarization encoding method using the polarization characteristics of LCDs. The results of XOR operations which are detected by a CCD camera should be used as an input to the JTC for comparison with a data base. We have verified the idea proposed here with computer simulations and the simulation results were also shown.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2036-2038
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• 2001

In this paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using vision system. In the proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Also, we use R,G,B(red, green, blue) color image data and the gray image data to get the highly trust rate of feature point extraction. For this, we propose an algorithm to extract four feature points (eyebrow, eye, nose, mouth) from the face image acquired by the color CCD camera and find some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector(position and distance among the feature points). Finally, we show the practical application possibility of the proposed method.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.29-34
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• 2021

In this paper, for efficient parking control, in an Arduino environment, an intelligent parking control prototype was implemented to provide parking control and parking guidance information using HC-SR2O4 and RC522. The main elements of intelligent parking control are vehicle recognition sensors, parking control facilities, and integrated operating software. Whether the vehicle is parked on the parking surface may be confirmed through sensor or intelligent camera image analysis. Parking control equipment products include parking guidance and parking available display devices, vehicle number recognition cameras, and intelligent parking assistance systems. This paper applies and implements ultrasonic sensors and RFID concepts based on Arduino, recognizes registered vehicles, and displays empty spaces. When a vehicle enters a parking space to handle this function, the automatic parking management system distinguishes the registered vehicle from the external vehicle through the RC522 sensor. In addition, after checking whether the parking slot is empty, the HC-SR204 sensor is displayed through the LED so that the driver can visually check it. RFID is designed to check the parking status of the server in real time and provide the driver with optimal route service to the parking slot.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.2
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• pp.105-111
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• 2021

The main source of underwater radiated noise of ships is cavitation generated by propeller blades. After the Cavitation Inception Speed (CIS), noise level at all frequencies increases severely. In determining the CIS, it is based on the results observed with the naked eye during the model test, however accuracy and consistency of CIS values are becoming practical issues. This study was carried out with the aim of developing a technology that can automatically recognize cavitation images using deep learning technique based on a Convolutional Neural Network (CNN). Model tests on a three-dimensional hydrofoil were conducted at a cavitation tunnel, and tip vortex cavitation was strictly observed using a high-speed camera to obtain analysis data. The results show that this technique can be used to quantitatively evaluate not only the CIS, but also the amount and rate of cavitation from recorded images.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• The Journal of Sustainable Design and Educational Environment Research
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• v.9 no.3
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• pp.1-11
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• 2010

In the construction industry, IT based information system has been diversely applied to increase productivity. Although IT device such as PDA, RFID, Barcode, wireless network and web camera has been introduced to gather information in construction site, the effect of the IT device is limited, because of bringing about additional works of engineer. In this paper, we proposed a defect management system which is based on handwritten document digitalization framework for introducing applicability of new IT device, digital pen. By the proposed system, we can effectively gather and input defect information to defect management system by using digital pen and paper like conventional way. Applying the data gathering device, digital pen to defect management, it is able to increase productivity by improving work process, building up and utilizing defect information database of good quality.

• Transactions of Materials Processing
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• v.11 no.7
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• pp.620-627
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• 2002

The purpose of this paper is the development of an automated measurement system for micro spring based on the digital image processing technique. This micro spring can be used in various engineering applications such as filament, load bearing springs, hard disk suspension and many others. Main functionality of the micro spring inspection system is to measure the representative pitch of the micro spring. The derivative operators are used for edge detection in gray level image. Measurement system developed in this paper consisted of new auto feeding mechanism to take advantage of air pressure. In the process of development of the micro spring inspection system based on the image processing and analysis, strong background technology and know-how have been accumulated to measure micro mechanical parts.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.3
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• pp.133-142
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• 2019

The existing auxiliary communicating aids for the hearing-impaired have an inconvenience of using additional expensive sensing devices. This paper presents a hand image detection based algorithm to interpret the sign language of the hearing-impaired. The proposed sign language recognition system exploits the hand image only captured by the camera without using any additional gloves with extra sensors. Based on the hand image processing, the system can perfectly classify several numeric sign language representations. This work proposes a simple lightweight classification algorithm to identify the hand image of the hearing-impaired to communicate with others even further in an environment of complex background. Experimental results show that the proposed system can interpret the numeric sign language quite well with an accuracy of 95.6% on average.