• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.263-266
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• 2013

표는 중요한 정보를 함축적으로 담고 있는 문서 요소로서 문서 영상에서 표의 내용과 구조를 분석하고 이해하려는 연구가 많이 진행되어 왔다. 이러한 표의 검출과 인식에 관한 기존의 연구들은 평판 스캐너로 취득한 문서 영상을 대상으로 이루어졌는데 최근에는 디지털 카메라와 스마트폰이 보급됨에 따라 평판 스캐너 대신 카메라를 이용한 표 인식의 필요성이 대두되고 있다. 따라서 본 논문에서는 카메라로 획득한 문서 영상에서 표 인식에 대한 알고리듬을 제안한다. 먼저 표가 선들의 집합으로 이루어져 있다는 가정 아래 문서 이미지에 존재하는 선을 이진화와 강인한 곡선 맞춤 알고리듬을 사용하여 검출한다. 검출된 선들의 교차점은 표의 요소일 수도 있으며 오검출의 결과일 수도 있는데 교차점 주변의 관찰 결과와 교차점 사이의 연관 관계를 에너지 식으로 표현하고 이 식을 최소화함으로써 각각의 교차점에 최적의 레이블을 할당한다. 얻어진 레이블은 표로 유일하게 변환되며 표의 구조를 셀 단위까지 추정할 수 있다. 다양한 표 영상에 대한 실험 결과를 통하여 제안한 방법이 문서영상의 기하학적인 왜곡에도 불구하고 영상에 존재하는 표를 성공적으로 인식함을 보여준다.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.95-101
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• 2016

In this study, we propose a new system for constructing parallel corpora for sign languages, which are generally under-resourced in comparison to spoken languages. In order to achieve scalability and accessibility regarding data collection and corpus construction, our system utilizes deep learning-based techniques and predicts depth information to perform pose estimation on hand information obtainable from video recordings by a single RGB camera. These estimated poses are then transcribed into expressions in SignWriting. We evaluate the accuracy of hand tracking and hand pose estimation modules of our system quantitatively, using the American Sign Language Image Dataset and the American Sign Language Lexicon Video Dataset. The evaluation results show that our transcription system has a high potential to be successfully employed in constructing a sizable sign language corpus using various types of video resources.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.57-65
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• 2010

Recently, the character recognization technique is strongly needed to enable the mobile communication devices with cameras to gather input information from the users. In general, it is not easy to reuse a CBOCR(Camera Based Optical Character Recognizer) module because of its dependency on a specific platform. In this paper, we propose a software architecture for CBOCR module providing the easy adaptability to various mobile communication platforms. The proposed architecture is composed of the platform dependency support layer, the interface layer, the engine support layer, and the engine layer. The engine layer adopts a plug-in data structure to support various hardware endian policies. We show the effectiveness of the proposed method by applying the architecture to a practical product.

• Journal of KIISE
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• v.41 no.9
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• pp.633-641
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• 2014

This paper proposes algorithms to detect jump motion and automatically take a picture when the jump reaches its top. Based on the algorithms, we build jump-shot system by using accelerometer-equipped smart phones. Since the jump motion may vary depending on one's physical condition, gender, and age, it is critical to figure out common features which are independent from such differences. Also it is obvious that the detection algorithm needs to work in real-time because of the short duration of the jump. We propose two different algorithms considering these requirements and develop the system as a smart phone application. Through a series of experiments, we show that the system is able to successfully detect the jump motion and take a picture when it reaches the top.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.171-178
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• 2010

The surveillance system in general, has been sufficiently studied in the field of wireless semiconductor using basic sensors and its study of image surveillance system mainly using camera as a sensor has especially been fully implemented. In this paper, we propose 'Intelligent Image Detection System' used by image object identification technique based on the result analysis of various researches. This 'Intelligent Image Detection System' can easily trace and judge before and after a particular incident and ensure affirmative evidence and numerous relative information. Therefore, the 'Intelligent Image Detection System' proposed in this paper can be effectively used in the lived society such as traffic management, disaster alarm system and etc.

• Journal of Auto-vehicle Safety Association
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• v.7 no.4
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• pp.26-30
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• 2015

Exceeding the speed limit during vehicle driving is a key factor in the severity of lots of road accidents, and SLIF(Speed Limit Information Function) application is in the initial phase in Korea. SLIF helps the drivers to observe a speed limit when they are driving by providing alert and informing the current limit speed information based on external data using camera and/or digital map, for that reason, environmental conditions could be causes of SLIF malfunctions. In this study, design adequacy analysis of SLIF in respect of false recognition as the Korea traffic environment has been performed. As tentative results, road conditions and structure of speed limit sign as well as system performance often caused misrecognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.816-819
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• 2011

The image recognition system using CCTV camera has been introduced to minimize not only loss of life and property but also traffic jam in the tunnel. In this paper, multi-object detection algorithm is proposed to track multi vehicles. The proposed algorithm is to detect multi cars based on Adaboost and to track multi vehicles to use template matching. As results of simulations, it is shown that proposed algorithm is useful for tracking multi vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1967-1983
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• 2020

The goal of this paper is to analyze and build an algorithm to recognize hand gestures applying to smart home applications. The proposed algorithm uses image processing techniques combing with artificial neural network (ANN) approaches to help users interact with computers by common gestures. We use five types of gestures, namely those for Stop, Forward, Backward, Turn Left, and Turn Right. Users will control devices through a camera connected to computers. The algorithm will analyze gestures and take actions to perform appropriate action according to users requests via their gestures. The results show that the average accuracy of proposal algorithm is 92.6 percent for images and more than 91 percent for video, which both satisfy performance requirements for real-world application, specifically for smart home services. The processing time is approximately 0.098 second with 10 frames/sec datasets. However, accuracy rate still depends on the number of training images (video) and their resolution.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1205-1211
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• 2008

This paper describes methods to estimate 3-D position of target with respect to reference frame through monocular image from unmanned aerial vehicle (UAV). 3-D position of target is used as information for surveillance, recognition and attack. In this paper. 3-D position of target is estimated to make guidance and control law, which can follow target, user interested. It is necessary that position of target is measured in image to solve 3-D position of target. In this paper, kalman filter is used to track and output position of target in image. Estimation of target's 3-D position is possible using result of image tracking and information of UAV and camera. To estimate this, two algorithms are used. One is methode from arithmetic derivation of dynamics between UAV, carmer, and target. The other is LPV (Linear Parametric Varying). These methods have been run on simulation, and compared in this paper.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.664-667
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• 2009

There is strong demand to create wearable PC systems that can support the user outdoors. When we are outdoors, our movement makes it impossible to use traditional input devices such as keyboards and mice. We propose a hand gesture interface based on image processing to operate wearable PCs. The semi-transparent PC screen is displayed on the head mount display (HMD), and the user makes hand gestures to select icons on the screen. The user's hand is extracted from the images captured by a color camera mounted above the HMD. Since skin color can vary widely due to outdoor lighting effects, a key problem is accurately discrimination the hand from the background. The proposed method does not assume any fixed skin color space. First, the image is divided into blocks and blocks with similar average color are linked. Contiguous regions are then subjected to hand recognition. Blocks on the edges of the hand region are subdivided for more accurate finger discrimination. A change in hand shape is recognized as hand movement. Our current input interface associates a hand grasp with a mouse click. Tests on a prototype system confirm that the proposed method recognizes hand gestures accurately at high speed. We intend to develop a wider range of recognizable gestures.