• 한국정보통신학회논문지
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• 제15권9호
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• pp.2007-2012
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• 2011

블록정합에서 방대한 계산을 줄이기 위해, 본 논문은 탐색영역에서 탐색점을 제한하는 고속 블록정합 알고리즘을 제안한다. 대부분의 움직임 벡터가 탐색영역 중심부에 위치하고, 정합오차가 최적의 유사블록을 향해 단조감소한다는 사실에 근거하여 제안된 알고리즘은 단계 사이에 정합패턴을 1 화소 단위로 이동하고, 이전 단계들에서 결정된 유사블록들로부터 최적의 유사블록을 향한 움직임을 예측하고, 탐색점들의 움직임을 움직임 방향에 대해 ${\pm}45^{\circ}C$로 제한한다. 그 결과 불필요한 탐색점을 제거할 수 있었고 블록정합 계산을 줄일 수 있었다. 기존 유사 고속 알고리즘과 비교하여 제안된 알고리즘은 큰 움직임을 갖는 영상에서 미미한 화질 저하를 발생시키지만 보통 움직임을 갖는 영상에서 동등한 화질을 유지하고, 반면에 그들의 블록정합 계산을 적게는 20% 많게는 67%를 줄여 주었다.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.1025-1031
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• 2000

Pre-existing pattern recognition techniques, in the case of character recognition, have limited on the application field. But CAI character learning system and writer's recognition system are very important parts. The application field of pre-existing system can be expanded in the content that the learning of characters and the recognition of writers in the proposed paper. In order to achieve these goals, the development contents are the following: Firstly, pre-processing method by understanding the image structure is proposed, secondly, recognition of characters are accomplished b the histogram distribution characteristics. Finally, similarity measure functions are defined from standard character pattern for matching of the input character pattern. Also the effectiveness of this system is demonstrated by experimenting the standard primitive image.

• Journal of Biosystems Engineering
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• 제27권2호
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.

• Journal of Ecology and Environment
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• 제43권4호
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• pp.385-389
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• 2019

Knowledge of abundance, or population size, is fundamental in wildlife conservation and management. Camera-trapping, in combination with capture-recapture methods, has been extensively applied to estimate abundance and density of individually identifiable animals due to the advantages of being non-invasive, effective to survey wide-ranging, elusive, or nocturnal species, operating in inhospitable environment, and taking low labor. We assessed the possibility of using coat patterns from images to identify an individual leopard cat (Prionailurus bengalensis), a Class II endangered species in South Korea. We analyzed leopard cat images taken from Digital Single-Lense Relfex camera (high resolution, 18Mpxl) and camera traps (low resolution, 3.1Mpxl) using HotSpotter, an image matching algorithm. HotSpotter accurately top-ranked an image of the same individual leopard cat with the reference leopard cat image 100% by matching facial and ventral parts. This confirms that facial and ventral fur patterns of the Amur leopard cat are good matching points to be used reliably to identify an individual. We anticipate that the study results will be useful to researchers interested in studying behavior or population parameter estimates of Amur leopard cats based on capture-recapture models.

• 전자공학회논문지A
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• 제33A권5호
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• pp.203-211
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• 1996

This paper describes CAD tools for the construction of image database in IC chip analysis CAD system. For IC chip analysis by high-resolution microscopy, the image database is essential to manage more than several thousand images. But manual database construction is error-prone and time-consuming. In order to solve this problem, we develop a set of CAD toos that include image grabber to capture chip images, image editor to make the whole chip image database from the grabbed images, and image divider to reconstruct the database that consists of evenly overlapped images for efficient region search. we also develop an interactive pattern matching method for user-friendly image editing, and a heuristic region search method for fast image division. The tools are developed with a high-performance graphic hardware with JPEG image comparession chip to process the huge color image data. The tools are under the field test and experimental resutls show that the database construction time can be redcued in 1/3 compared to manual database construction.

• 대한기계학회논문집A
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• 제23권11호
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• pp.1929-1939
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• 1999

This paper presents a neural network approach, which was named PRONET, to 3D object recognition and pose calculation. 3D objects are represented using a set of centroidal profile patterns that describe the boundary of the 2D views taken from evenly distributed view points. PRONET consists of the training stage and the execution stage. In the training stage, a three-layer feed-forward neural network is trained with the centroidal profile patterns using an error back-propagation method. In the execution stage, by matching a centroidal profile pattern of the given image with the best fitting centroidal profile pattern using the neural network, the identity and approximate orientation of the real object, such as a workpiece in arbitrary pose, are obtained. In the matching procedure, line-to-line correspondence between image features and 3D CAD features are also obtained. An iterative model posing method then calculates the more exact pose of the object based on initial orientation and correspondence.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.601-605
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• 2009

We have proposed a measurement system for measuring a whole shape of an object easily. The proposed system consists of a camera and a cylinder whose inside is coated by a mirror layer. A target object is placed inside the cylinder and an image is captured by the camera from right above. The captured image includes sets of points that are observed from multiple viewpoints: one is observed directly, and others are observed via the mirror. Therefore, the whole shape of the object can be measured using stereo vision in a single shot. This paper shows that a prototype of the proposed system was implemented and an actual object was measured using the prototype. A method based on a pattern matching which uses a value of SSD (Sum of Squared Difference), and a method based on DP (Dynamic Programming) are employed to identify a set of corresponding points in warped captured images.

• 한국산학기술학회논문지
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• 제4권2호
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• pp.87-95
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• 2003

Dynamic Programming Matching (DPM)은 순차적으로 구성된 문제를 수학적으로 최적화 시키는 기술로서 패턴인시 분야에서 다년간 중요한 역할을 해왔다. 서명인식을 위한 대부분의 실제적 적용에서는 Sakoe and Chiba [9]의 실제구현 버전이 기반이 되어 왔는데, 일반적으로 slope constraint p = 0의 방법이 적용되어 왔다. 이 논문에서는 이 경우에는 전진탐색에 의한 휴리스틱한 방법을 적용한 MDPM이 상당한 처리시간의 단축 뿐만 아니라 약간의 인식능력 향상을 가질 수 있음을 보여준다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (C)
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• pp.263-266
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• 2007

We introduce a vision-based hand gesture recognition fer understanding musical time and patterns without extra special devices. We suggest a simple and reliable vision-based hand gesture recognition having two features First, the motion-direction code is proposed, which is a quantized code for motion directions. Second, the conducting feature point (CFP) where the point of sudden motion changes is also proposed. The proposed hand gesture recognition system extracts the human hand region by segmenting the depth information generated by stereo matching of image sequences. And then, it follows the motion of the center of the gravity(COG) of the extracted hand region and generates the gesture features such as CFP and the direction-code finally, we obtain the current timing pattern of beat and tempo of the playing music. The experimental results on the test data set show that the musical time pattern and tempo recognition rate is over 86.42% for the motion histogram matching, and 79.75% fer the CFP tracking only.

• 방송공학회논문지
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• 제17권3호
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• pp.437-446
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• 2012

흑백 혹은 컬러 영상과 같은 2차원 정보를 사용한 얼굴 검출 알고리즘에 관한 연구가 수십 년 동안 이루어져 왔다. 최근에는 저가 range 센서가 개발되어, 이를 통해 3차원 정보 (깊이 정보: 카메라와 물체사이의 거리를 나타냄)를 손쉽게 이용함으로써 얼굴의 특징을 높은 신뢰도로 추출하는 것이 가능해졌다. 대부분 사람 얼굴에는 3차원적인 얼굴의 구조적인 특징이 있다. 본 논문에서는 흑백 영상과 깊이 영상을 사용하여 얼굴을 검출하는 알고리즘을 제안한다. 처음에는 흑백 영상에 adaboost를 적용하여 얼굴 후보 영역을 검출한다. 얼굴 후보 영역의 위치에 대응되는 깊이 영상에서의 얼굴 후보 영역을 추출한다. 추출된 영역의 크기를 $5{\times}5$ 영역으로 분할하여 깊이 값의 평균값을 구한다. 깊이 값들의 평균값들 간에 순위를 매김으로써 블록 순위 패턴이 생성된다. 얼굴 후보 영역의 블록 순위 패턴과 학습 데이터를 사용하여 미리 학습된 템플릿 패턴을 매칭함으로써 최종 얼굴 영역인지 아닌지를 판단할 수 있다. 제안하는 방법의 성능을 Kinect sensor로 취득한 실제 영상으로 실험하였다. 실험 결과 true positive를 잘 보존하면서 많은 false positive들을 효과적으로 제거하는 것을 보여준다.