• Journal of Advanced Navigation Technology
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• v.2 no.2
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• pp.107-115
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• 1998

In this paper, we propose a robust moving object tracking(MOT) method based on motion energy and prediction. MOT consists of two steps: moving object extraction step(MOES) and moving object tracking step(MOTS). For MOES, we use improved motion energy method. For MOTS, we predict the next location of moving object based on distance and direction information among previous instances, so that we can reduce the search space for correspondence. We apply the method to both synthetic and real world sequences and find that the method works well even in the presence of occlusion and disocclusion.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.31-38
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• 2005

This paper proposes an object-based image retrieval scheme using color adjacency and clustering method. Color adjacency features in boundary regions are utilized to extract candidate blocks of interest from image database and a clustering method is used to extract the regions of interest(ROI) from candidate blocks of interest. To measure the similarity between the query and database images, the histogram intersection technique is used. The color pair information used in the proposed method is robust against translation, rotation, and scaling. Consequently, experimental results have shown that the proposed scheme is superior to existing methods in terms of ANMRR.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.415-418
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• 2007

본 논문은 머리카락을 포함한 얼굴 영역 추출에 관한 것으로서, 보다 구체적으로는 조명변화에도 강인 한 얼굴영역 추출방법과 다양한 머리카락의 모양과 색의 변화에도 신뢰성 있는 머리카락 추출 방법에 관한 것이다. 일반적으로 얼굴영상은 개인의 특징을 잘 표현할 수 있는 정보로써, 영상에서 얼굴 영역을 추출하여 이를 실제 얼굴영상정보를 이용한 얼굴인식, 관상정보 서비스를 위한 전처리, 기반기술을 제공하고, 실사 캐릭터 제작에도 바로 적용될 수 있다. 기존의 템플리트 매칭, 곡선추적 알고리즘 등과의 같은 추출방법에서는 얼굴크기 변화, 안경 및 장신구의 착용 여부 그리고 조명의 변화에 따라 얼굴영역 추출하는 처리속도가 많이 걸리고, 성능이 크게 저하되는 문제점이 있다. 상기한 바와 같이 종래의 문제점을 개선하기 위하여, 본 논문에서는 얼굴의 크기변화, 안경 및 장신구의 착용 여부 그리고 조명의 변화에서도 얼굴 영역을 잘 추출 할 있는 방법과 다양한 머리카락의 색, 형태 변화에도 신뢰성 있는 머리카락 추출방법을 제안하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.107-112
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• 2016

Fastener is a very important component that is used in various areas in industry. Recently, various color fasteners are introduced. According to this, online inspection is required in this area. In this paper, an algorithm for the automatic extraction of the surface of color fastener using color information and dynamic programming is presented. The outer boundary of fastener is found using the difference of color that enables robust processing. The inner boundary of fastener is found by dynamic programming that uses the difference of brightness value within fixed area after converting image to polar coordinate. Experiments are done using the same parameters.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.6
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• pp.528-534
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• 2005

Hairy root cultures have demonstrated great promise in terms of their biosynthetic capability toward the production of secondary metabolites, but continue to constitute a major challenge with regard to large-scale cultures. In order to assess the possibility of conducting mass production of biomass, and the extraction of useful metabolites from Panax ginseng. P. ginseng hairy roots, transformed by Rhizobium rhizogenes KCTC 2744, were used in bioreactors of different types and sizes. The most effective mass production of hairy roots was achieved in several differently Sized air bubble bioreactors compared to all other bioreactor types. Hairy root growth was enhanced by aeration, and the production increased with increasing aeration rate in a 1 L bioreactor culture. It was determined that the hairy root growth rate could be substantially enhanced by increases in the aeration rate upto 0.5vvm, but at aeration rates above 0.5vvm, only slight promotions in growth rates were observed. In 20 L air bubble bioreactors, with a variety of inoculum sizes, the hairy roots exhibited the most robust growth rates with an inoculum size of 0.1% (w/v), within the range 0.1 to 0.7% (w/v). The specific growth rates of the hairy root decreased with increases in the inoculum size.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.601-607
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• 2012

The recognition of elevator door is needed for mobile service robots to moving between floors in the building. This paper proposed the sensor fusion approach using LRF (Laser Range Finder) and camera to solve the problem. Using the laser scans by the LRF, we extract line segments and detect candidates as the elevator door. Using the image by the camera, the door candidates are verified and selected as real door of the elevator. The outliers are filtered through the verification process. Then, the door state detection is performed by depth analysis within the door. The proposed method uses extrinsic calibration to fuse the LRF and the camera. It gives better results of elevator door recognition compared to the method using LRF only.

• ETRI Journal
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• v.28 no.6
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• pp.721-731
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• 2006

A fast intra skip detection algorithm based on the ratedistortion (RD) cost for an inter frame (P-slices) is proposed for H.264/AVC video encoding. In the H.264/AVC coding standard, a robust rate-distortion optimization technique is used to select the best coding mode and reference frame for each macroblock (MB). There are three types of intra predictions according to profiles. These are $16{\times}16$ and $4{\times}4$ intra predictions for luminance and an $8{\times}8$ intra prediction for chroma. For the high profile, an $8{\times}8$ intra prediction has been added for luminance. The $4{\times}4$ prediction mode has 9 prediction directions with 4 directions for $16{\times}16$ and $8{\times}8$ luma, and $8{\times}8$ chrominance. In addition to the inter mode search procedure, an intra mode search causes a significant increase in the complexity and computational load for an inter frame. To reduce the computational load of the intra mode search at the inter frame, the RD costs of the neighborhood MBs for the current MB are used and we propose an adaptive thresholding scheme for the intra skip extraction. We verified the performance of the proposed scheme through comparative analysis of experimental results using joint model reference software. The overall encoding time was reduced up to 32% for the IPPP sequence type and 35% for the IBBPBBP sequence type.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.95-101
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• 1999

In this paper, we propose an adaptive method of tracking multiple moving objects using contour and features in surrounding conditions. We use an adaptive background model for robust processing in surrounding conditions. Object segmentation model detects pixels thresholded from local difference image between background and current image and extracts connected regions. Data association problem is solved by using feature extraction and object recognition model in searching window. We use Kalman filters for real-time tracking. The results of simulation show that the proposed method is good for tracking multiple moving objects in highway image sequences.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.23-30
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• 2014

Feature matching using image descriptors is robust method used recently. However, mismatches occur in 3D transformed images, illumination-changed images and repetitive-pattern images. In this paper, we observe that there are a lot of mismatches in the images which have repetitive patterns. We analyze it and propose a method to eliminate these mismatches. MDMF(Multiple Descriptors-based Mismatch Filtering) eliminates mismatches by using descriptors of nearest several features of one specific feature point. In experiments, for geometrical transformation like scale, rotation, affine, we compare the match ratio among SIFT, ASIFT and MDMF, and we show that MDMF can eliminate mismatches successfully.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.111-119
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• 2013

Face recognition has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous applications, such as access control, surveillance, security, credit-card verification, and criminal identification. In this paper, we propose a simple descriptor called an ECSP(Extended Center-Symmetric Pattern) for illumination-robust face recognition. The ECSP operator encodes the texture information of a local face region by emphasizing diagonal components of a previous CS-LBP(Center-Symmetric Local Binary Pattern). Here, the diagonal components are emphasized because facial textures along the diagonal direction contain much more information than those of other directions. The facial texture information of the ECSP operator is then used as the input image of an image covariance-based feature extraction algorithm such as 2D-PCA(Two-Dimensional Principal Component Analysis). Performance evaluation of the proposed approach was carried out using various binary pattern operators and recognition algorithms on the Yale B database. The experimental results demonstrated that the proposed approach achieved better recognition accuracy than other approaches, and we confirmed that the proposed approach is effective against illumination variation.