• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제7권2호
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• pp.106-110
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• 2014

This paper proposed the face recognition method which can be effectively applied to the robot's vision system. The proposed algorithm is recognition using hue extraction and feature point. hue extraction was using difference of skin color, pupil color, lips color. Features information were extraction from eye, nose and mouth using feature parameters of the difference between the feature point, distance ratio, angle, area. Feature parameters fuzzified data with the data generated by membership function, then evaluate the degree of similarity was the face recognition. The result of experiment are conducted with frontal color images of face as input images the received recognition rate of 96%.

• Journal of the Institute of Convergence Signal Processing
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• 제1권1호
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• pp.42-48
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• 2000

In this paper, we propose the face image recognition algorithm using skin color information, face region features such as eye, nose, and mouse, etc., and geometrical features of chin line. In the proposed algorithm, we used the intensity as well as skin color information in the HSI color coordinate which is similar to human eye system. The experimental results of proposed method shows improved extraction quality of face and provides adaptive extraction methods for the races. And also, we used chin line information as well as geometrical features of face such as eye, nose, mouse information for the improvement of face recognition quality, Experimental results shows the more improved recognition as well as extraction quality than conventional methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제14권2호
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• pp.885-892
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• 2013

In this paper, we propose a method of effectively segmenting character regions by using texture and depth features in 3D stereoscopic images. The suggested method is mainly composed of four steps. The candidate character region extraction step extracts candidate character regions by using texture features. The character region localization step obtains only the string regions in the candidate character regions. The character/background separation step separates characters from background in the localized character areas. The verification step verifies if the candidate regions are real characters or not. In experimental results, we show that the proposed method can extract character regions from input images more accurately compared to other existing methods.

• Journal of Intelligence and Information Systems
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• 제8권2호
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• pp.1-13
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• 2002

In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.

• Journal of the Korea Society of Computer and Information
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• 제15권12호
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• pp.27-35
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• 2010

Extracting skin color is significant in adult image detection. However, conventional methods still have essential problems in extracting skin color. That is, colors of human skins are basically not the same because of individual skin difference or difference races. Moreover, skin regions of images may not have identical color due to makeup, different cameras used, etc. Therefore, most of the existing methods use predefined skin color models. To resolve these problems, in this paper, we propose a new adult image detection method that robustly segments skin areas with an input image-adapted skin color distribution model, and verifies if the segmented skin regions contain naked bodies by fusing several representative features through a neural network scheme. Experimental results show that our method outperforms others through various experiments. We expect that the suggested method will be useful in many applications such as face detection and objectionable image filtering.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제29권6C호
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• pp.834-841
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• 2004

There can be lips transformed geometrically in the lip images according to the location or the pose of camera and speaker. This transformation of the lip images changes geometric information of original lip phases. Therefore, for enhancing global lip information by using partial information of lips to correct lip phases transformed geometrically, in this paper we propose a method that can geometrically correct lips. The method is composed of two steps - the feature-deciding step and the correcting step. In the former, it is for us to extract key points and features of source image according to the its lip model and to create that of target image according to the its lip model. In the latter, we decide mapping relation after partition a source and target image based on information extracted in the previous step into each 4 regions. and then, after mapping, we unite corrected sub-images to a result image. As experiment image, we use fames that contain pronunciation on short vowels of the Korean language and use lip symmetry for evaluating the proposed algorithm. In experiment result, the correcting rate of the lower lip than the upper lip and that of lips moving largely than little was highly enhanced.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.605-608
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• 2010

두 영상에서 특징점을 추적하기 위하여 특징점을 중심으로 $N{\times}N$ 크기 윈도우 패치의 SSD 값을 비교하는 방법을 사용한다. 그러나 영상에서 다수의 특징점이 추출되어 매칭을 시도하는 경우 많은 처리 시간을 필요로 한다. 처리 시간의 증가는 실시간 처리를 어렵게 만든다. 이러한 문제를 해결하기 위하여 적분 영상(integral image)을 사용하여 매칭 가능성이 높은 특징점을 필터링하여 SSD 매칭의 처리 시간을 단축시키는 방법을 제안한다. 본 논문에서 제안한 적분 영상을 사용한 특징점 필터링을 적용한 방법과 기존의 SSD 매칭 방법을 비교 실험하여 특징점 매칭의 처리 시간을 절감하는 결과를 얻을 수 있었다.

• Journal of Korea Multimedia Society
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• 제16권9호
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• pp.1057-1066
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• 2013

Personal verification using finger-knuckle-print(FKP) uses lines and creases at the finger-knuckle area, so the orientation information of texture is an important feature. In this paper, we propose an effective FKP verification method which extracts keypoints using SIFT algorithm and matches the keypoints by vector similarity. The vector is defined as a direction vector which connects a keypoint extracted from a query image and a corresponding keypoint extracted from a reference image. Since the direction vector is created by a pair of local keypoints, the direction vector itself represents only a local feature. However, it has an advantage of expanding a local feature to a global feature by comparing the vector similarity among vectors in two images. The experimental results show that the proposed method is superior to the previous methods based on orientation codes.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (2)
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• pp.544-546
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• 2003

홍채인식 기술에서 홍채영역 추출 방법은 필요한 데이터를 추출, 변환하는 과정에서 발생하는 홍채정보의 손실을 최소화하는데 그 목적이 있다. 그러나 기존의 홍채인식에서 사용되는 홍채영역 추출 방법은 초기 눈 영상 획득 시 얻은 영상의 눈 기울기가 일정하다는 가정에 기초하거나, 하나의 홍채 데이터를 기준으로 삼고, 다른 홍채데이터를 비교하여 기울기를 보정하기 때문에 동일인에게서 취득한 영상이라 하더라도 영상간의 기울기가 크다면 두 홍채 데이터의 공통된 특징 역시 상대적으로 적거나 차이가 날 수밖에 없다. 결국, 이는 실제 필드에서 사용할 시스템의 인식률에 영향을 줄 수밖에 없다. 본 논문에서는 이 문제를 보완하기 위한 방안으로, 눈 영상 내에서 내안각을 찾아내고 이를 기준으로 하여, 눈 영상의 특정 부분에서 일정한 홍채영역을 추출하는 방법을 제안한다. 본 논문에서는 우리가 제안하는 방법을 사용하여 실제 취득한 모든 눈 영상에 대한 실험을 한 결과, 비교적 일정한 홍채영역을 추출할 수 있음을 입증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2003년도 춘계학술발표논문집 (상)
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• pp.691-694
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• 2003

게이트는 사람의 걷는 방법 혹은 그 특성을 나타내는 용어로써, 최근 컴퓨터 비젼 기술을 이용하여 개개인을 분별하기 위한 게이트 특징 정보를 추출하고자 하는 연구가 활발히 진행되고 있다. 그러나 영상을 기반으로 추출한 게이트 정보는 카메라의 시점에 종속적인 단점을 가지고 있다. 이러한 단점을 해결하기 위한 노력으로 3차원 정보를 획득하려는 연구가 진행되고 있으나 이는 카메라와 사람간의 거리, 카메라 파라미터 등 부가적인 정보를 필요로 한다. 본 논문에서는 영상내의 정보만을 이용하여, 카메라 시점에 종속적인 게이트 인식의 단점을 해결할 수 있는 방안을 제안한다. 먼저 실루엣 영상으로부터 걷는 방향을 찾아내고, 간단한 연산을 통해 평면 호모그래피를 추정한다. 추정된 호모그래피를 이용하여 측면 시점의 영상으로 재구성하면, 시점 변화에 비종속적인 게이트 정보를 추출할 수 있다. 본 논문에서 제안한 방법을 평가하기 위하여 실추엣 영상의 폭과 높이 변화를 비교하였다 실험을 통해 제안한 방법을 적용할 경우, 그렇지 않은 경우에 비하여 특징 변화가 적음을 확인하였고, 특히 보폭 통의 게이트 특징 정보가 일정한 값을 유지함을 볼 수 있었다.