• Journal of Information Processing Systems
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• 제11권4호
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• pp.601-615
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• 2015

Region of interest (ROI) is the most informative part of a medical image and mostly has been used as a major part of watermark. Various shapes ROIs selection have been reported in region-based watermarking techniques. In region-based watermarking schemes an image region of non-interest (RONI) is the second important part of the image and is used mostly for watermark encapsulation. In online healthcare systems the ROI wrong selection by missing some important portions of the image to be part of ROI can create problem at the destination. This paper discusses the complete medical image availability in original at destination using the whole image as a watermark for authentication, tamper localization and lossless recovery (WITALLOR). The WITALLOR watermarking scheme ensures the complete image security without of ROI selection at the source point as compared to the other region-based watermarking techniques. The complete image is compressed using the Lempel-Ziv-Welch (LZW) lossless compression technique to get the watermark in reduced number of bits. Bits reduction occurs to a number that can be completely encapsulated into image. The watermark is randomly encapsulated at the least significant bits (LSBs) of the image without caring of the ROI and RONI to keep the image perceptual degradation negligible. After communication, the watermark is retrieved, decompressed and used for authentication of the whole image, tamper detection, localization and lossless recovery. WITALLOR scheme is capable of any number of tampers detection and recovery at any part of the image. The complete authentic image gives the opportunity to conduct an image based analysis of medical problem without restriction to a fixed ROI.

• 제어로봇시스템학회논문지
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• 제16권12호
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• pp.1226-1232
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• 2010

A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.

• 전자공학회논문지
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• 제52권9호
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• pp.89-95
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• 2015

본 논문에서는 비전 기술을 기반으로 원거리에서 2차원 바코드를 검출 할 수 있는 실시간 시스템을 제안한다. 제안된 시스템은 2차원 바코드의 위치 심볼을 찾는 근거리 검출을 먼저 수행하고, 만약 검출이 안 될 경우 원거리 검출로 전환된다. 원거리 검출은 다음과 같은 순서로 진행된다. 먼저 에지 지도, 영상 이진화, CCL(connect component labeling)을 순차적으로 수행하여 관심 영역을 설정한다. 설정된 관심 영역을 Bilinear Interpolation을 이용하여 확대한 후, 근거리 검출과 마찬가지로 위치 심볼 패턴을 검출하여 2차원 바코드 영역을 결정한다. 마지막으로 검출된 패턴 정보를 활용하여 역 투영 변환을 적용하여 패턴을 정렬하게 된다. 실험 결과 제안된 시스템은 기존에 제안된 2차원 검출 알고리즘보다 약 2~3배정도 더 먼 거리의 바코드를 검출 할 수 있음을 보였고, 여러 개의 2차원 바코드 검출이 가능함을 보였다. 또한, 실내의 복잡한 환경에서도 강인한 검출 결과를 보였다.

• Journal of the Optical Society of Korea
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• 제19권5호
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• pp.467-476
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• 2015

Finger vein recognition, which is a promising biometric method for identity authentication, has attracted significant attention. Considerable research focuses on transmission-type finger vein recognition, but this type of authentication is difficult to implement in mobile consumer devices. Therefore, reflection-type finger vein recognition should be developed. In the reflection-type vein recognition field, the majority of researchers concentrate on palm and palm dorsa patterns, and only a few pay attention to reflection-type finger vein recognition. Thus, this paper presents reflection-type finger vein recognition for biometric application that can be integrated into mobile consumer devices. A database is built to test the proposed algorithm. A novel method of region-of-interest localization for a finger vein image is introduced, and a scheme for effectively extracting finger vein features is proposed. Experiments demonstrate the feasibility of reflection-type finger vein recognition.

• 전자공학회논문지
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• 제52권8호
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• pp.132-139
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• 2015

카메라를 이용하는 시각(visual) SLAM(Simultaneous Localization And Mapping)은 로봇의 위치 등을 파악하는데 널리 이용되고 있다. 일반적으로 시각 SLAM은 움직임이 없는 고정된 특징점을 대상으로 연속적인 시퀀스 상에서 카메라의 움직임을 추정한다. 따라서 이동하는 객체가 많이 존재하는 상황에서는 안정적인 결과를 기대하기 어렵다. 본 논문에서는 이동 객체가 많은 상황에서 스테레오 카메라를 이용한 SLAM을 안정화하는 방법을 제안한다. 먼저, 스테레오 카메라를 이용하여 깊이영상을 추출하고 옵티컬 플로우를 계산한다. 그리고 좌우 영상의 옵티컬 플로우를 이용하여 시차변화(disparity change)를 계산한다. 그리고 깊이 영상에서 사람과 같이 움직이는 객체에 대한 ROI(Region Of Interest)를 구한다. 실내 상황에서는 벽과 같은 정적인 평면들이 움직이는 영역으로 잘못 판단되는 경우가 자주 발생한다. 이런 문제점을 해결하기 위해 깊이 영상을 X-Z 평면으로 사영하고 허프(hough) 변환하여 장면을 구성하는 평면을 결정한다. 앞의 과정에서 판단된 이동 객체 중에서 벽과 같은 장면 요소를 제외한다. 제안된 방법을 통해 정적인 특징점이 요구되는 SLAM의 성능을 보다 안정화할 수 있음을 확인하였다.

• 로봇학회논문지
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• 제17권2호
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• pp.198-208
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• 2022

In this paper, an autonomous driving system is implemented for the Segye AI Robot Race Competition that multiple vehicles drive simultaneously. By utilizing the ERP42-racing platform, RTK-GPS, and LiDAR sensors provided in the competition, we propose an autonomous driving system that can drive safely and quickly in a road environment with multiple vehicles. This system consists of a recognition, judgement, and control parts. In the recognition stage, vehicle localization and obstacle detection through waypoint-based LiDAR ROI were performed. In the judgement stage, target velocity setting and obstacle avoidance judgement are determined in consideration of the straight/curved section and the distance between the vehicle and the neighboring vehicle. In the control stage, adaptive cruise longitudinal velocity control based on safe distance and lateral velocity control based on pure-pursuit are performed. To overcome the limited experimental environment, simulation and partial actual experiments were conducted together to develop and verify the proposed algorithms. After that, we participated in the Segye AI Robot Race Competition and performed autonomous driving racing with verified algorithms.