• Journal of Information Display
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• v.11 no.4
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• pp.169-172
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• 2010

This paper proposes a multi-touch detection technology that can be applied to large LCDs. To achieve this goal, a set of IR LEDs and sensors was used to construct an IR matrix, and a new algorithm based on Hough transform was applied. This approach reduced the "Ghost" response of the multi-touch detection technology to make it better than other IR touch recognition technologies, and showed robust performance in terms of multi-touch recognition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.578-583
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• 2017

This paper presents a 3D touch pad technology that uses force touch sensors as a next-generation method for mobile applications. 3D touch technology requires detecting the location and pressure of touches simultaneously, as well as multi-touch function. We used metal foil strain gauges for the touch recognition sensor and detected the weak touch signals using Wheatstone bridge circuit at each strain gauge sensor. We also developed a touch recognition system that amplifies touch signals, converts them to digital data through a microprocessor, and displays the data on a screen. In software, we designed a touch recognition algorithm with C code, which is capable of recognizing two-point touch and differentiating touch pressures. We carried out a successful experiment to display two touch signals on a screen with different forces and locations.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.13-18
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• 2010

Most of the research in the multi-touch area is based on the FTIR(Frustrated Total Internal Re리ection), which is just implemented by using the previous approach. Moreover, there are not the software solutions to improve a performance in the multi touch-blobs detection or the user gesture recognition. Therefore, we implement a multi-touch table-top display that is based on the DI(Diffused Illumination), the improved touch-points detection and user gesture recognition. The proposed method supports a simultaneous transformation multi-touch command for objects in the running application. Also, the system latency time is reduced by the proposed ore-testing method in the multi touch-blobs detection processing. Implemented device is simulated by programming the Flash AS3 application in the TUIO(Tangible User Interface Object) environment that is based on the OSC(Open Sound Control) protocol. As a result, Our system shows the 37% system latency reduction, and is successful in the multi-touch gestures recognition.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1759-1766
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• 2016

We can implement the virtual touch recognition system by mounting the virtual touch algorithm into an embedded device connected to a depth camera. Since the computing performance is limited in embedded system, the real-time processing of recognizing the virtual touch is difficult when the resolution of the depth image is large. In order to resolve the problem, this paper improves the algorithms of binarization and labeling that occupy a lot of time in all processing of virtual touch recognition. It processes the binarization and labeling in only necessary regions rather than all of the picture. By appling the proposed algorithm, the system can recognize the virtual touch in real-time as about 31ms per a frame in the depth image that has 640×480 resolution.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.136-140
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• 2014

This paper introduces a multi-touch recognition and tracking method for self capacitive TSP(Touch Screen Pannel). Self capacitive TSP recognizes finger touches by sensing capacitive change of ITO transparent conducting film arranged by rows and columns on the TSP pannel. They have some advantages such as high SNR, fast sensing, and simple touch processing, but have very difficulties for multi-touch processing. This disadvantage makes that the mutual capacitive TSPs, which have no such disadvantage, have been more widely used especially for multi-touch applications. However, since the other applications for remote control pad or recently developed wearable devises have only restrictive requirements for multi-touch, the disadvantage of self capacitive TSP is not a critical problem. In this paper, we first describe multi-touch recognition problems in self capacitive TSP and then propose how to overcome those problems and a tracking method of two touches when they are moving. Experimental results of our method showed that our algorithm works well in two touches.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.465-472
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• 2015

This paper presents a visual touch recognition for NUI(Natural User Interface) using Voronoi-tessellation algorithm. The proposed algorithms are three parts as follows: hand region extraction, hand feature point extraction, visual-touch recognition. To improve the robustness of hand region extraction, we propose RGB/HSI color model, Canny edge detection algorithm, and use of spatial frequency information. In addition, to improve the accuracy of the recognition of hand feature point extraction, we propose the use of Douglas Peucker algorithm, Also, to recognize the visual touch, we propose the use of the Voronoi-tessellation algorithm. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.141-146
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• 2014

This paper describes the implementation and algorithm of handwritten character recognition using mobile touch screen. The system is consisted of PXA320 processor, capacitive touch panel and QT4 interface. The proposed algorithm extracts pattern characteristics with straight, left circle, right circle on the inputting character. The definition of character is determined by 3-way tree searching method. The performance of proposed algorithm is verified using alphabet character. It is suitable to apply the mobile touch screen because of simple algorithm.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.69-75
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• 2013

This paper introduces a touch recognition method for touch screen systems based on the SIFT(Scale Invariant Feature Transform) algorithm for stable touch recognition under strong noises. This method provides strong robustness against the noises and makes it possible to effectively extract the various size of touches due to the SIFT algorithm. In order to verify our algorithm we simulate it on the Matlab with the channel data obtained from a real touch screen. It was found from the simulations that our method could stably recognize the touches without regard to the size and direction of the touches. But, our algorithm implemented on a real touch screen system does not support the realtime feature because the DoG(Difference of Gaussian) of the SIFT algorithm needs too many computations. We solved the problem using the DoM(Difference of Mean) which is a fast approximation method of DoG.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.169-172
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• 2009

In this paper, we propose the method to improving touch recognition using edge mask on a touched object at vision-based touchscreen. Because vision-based touchscreen recognizes touch using threshold simply, noise occur in fist or wrist in case of touch directly with hand, correct touch recognition was difficult. However, in this paper, we execute morphology and extract surrounding mask in object that approximate to touchscreen, use change of contrast for the mask. When we touch screen to use these dynamic information, prevent noise. The goal of this paper is when hand was touched on screen it can recognize to touch.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.348-353
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• 2008

This paper proposes a novel touch interface for recognizing user's touch pattern and understanding emotional information by eliciting natural user interaction. To classify physical touches, we represent the similarity between touches by analyzing touches based on its dictionary meaning and design the algorithm to recognize various touch patterns in real time. Finally we suggest the methodology to estimate user's emotional state based on touch.