• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.227-230
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• 2002

A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.236-239
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• 1997

Snakes is an active contour model or representing image contours. To detect chest boundary on thoracic MRI sequences, we proposed a method based on modified greedy algorithm. Because thoracic MRI sequences have a spatial correlation, we added energy term related with spatial correlation to Snakes energy formulation. A measure of shape similarity called the BMD was used to evaluate the accuracy of the algorithm. The average BMD value or the modified algorithm's result is higher than greedy algorithm's.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.246-251
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• 1998

This paper proposes a new building segmentation method from 1m resolution imagery using an Active Contour Model, known as "Balloons". The original balloons, which was designed by Cohen(Cohen, 1991) to extract features from medical images, are modified for building segmentation. The proposed method consists of two phases. Firstly, building boundaries are extracted by balloons with a given position on buildings from an operator. Since balloons actively adjust their shapes according to the boundaries, there is no more shape limitations on detecting buildings. Secondly, buildings are segmented by connecting the corners detected from the building boundaries, because most buildings, which are man-made objects, are effectively described by polygons. The test results show that most buildings are segmented efficiently and easily. The proposed method is new and timely as 1m resolution spaceborne imagery will be available in the very near future. The proposed method can be used fur operational building segmentation from such imagery.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.103-105
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• 2022

본 논문에서는 스네이크 알고리즘에서 복잡한 배경으로 인해 어긋난 윤곽선을 개선하는 방법을 제안한다. 스네이크 알고리즘은 능동 윤곽선 모델(active contour model)중 하나로, 사전 정의한 영역에서 시작하여 점진적으로 강한 변화가 감지되는 방향으로 윤곽선을 수정하는 방법이다. 그러나 이러한 방법은 강한 기울기 성분이 나타나는 배경에 취약하고, 대상의 불필요한 영역이 포함되거나, 필요한 영역이 포함되지 않는 문제가 발생한다. 제안하는 방법은 이미지에 원근 변환을 기반으로 한 스네이크 알고리즘을 반복적으로 적용하여 대상의 윤곽선을 온전히 추출한다. 이는 실험 데이터에서 평균 IoU가 약 11.5% 이상 증가한 것을 통해 올바른 윤곽선을 찾는데 효과적인 방법임을 알 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.

• Journal of Integrative Natural Science
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• v.8 no.4
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• pp.273-284
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• 2015

Chemoattractant Receptor Homologous molecule expressed on Th2 cells (CRTh2) is a chemoattractant receptor with seven transmembrane helices targeted for inflammatory diseases such as asthma and allergic rhinitis. In this study, pharmacophore based Comparative Molecular Similarity Indices Analysis (CoMSIA) were performed on the series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids derivatives. Initially, GASP module was used for generation of pharmacophore models using five highly active compounds from the dataset. Among the generated pharmacophores, the best pharmacophore model was selected based on fitness score and was used as template for the alignment of compounds which was used for CoMSIA analysis. The best predictions were obtained utilizing steric, hydrophobic and H-bond acceptor parameters showing a $q^2$=0.559 and $r^2$=0.730. 15 test set compounds was used to investigate the predictive ability of the CoMSIA model. Contour maps suggested that presence of bulky substituents and H-bond acceptor atoms at $5^{th}$ position of benzene ring will increase the activity of the compounds. The results obtained from this study will be useful to design more potent CRTh2 antagonists.

• Journal of Integrative Natural Science
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• v.8 no.2
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• pp.89-98
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• 2015

Chemoattractant receptor homologous molecule expressed on Th2 cells (CRTh2) is a G-protein coupled receptor targeted for inflammatory diseases such as asthma, allergic rhinitis and atopic dermatitis. In this study, pharmacophore modeling and comparative molecular field analysis (CoMFA) were performed on the series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids derivatives. Five highly active compounds were used for generation of pharmacophore models using GASP module. The best pharmacophore model was selected and used as template for the alignment of compounds which was used for CoMFA analysis. The best predictions obtained for CoMFA was $q^2=0.545$, $r^2=0.756$. The predictive ability of the model was investigated using 15 test set compounds. Contour maps suggested that presence of bulky substituents at $5^{th}$ position of benzene ring connected to suphur atoms attached to imidazol ring will increase the activity of the compounds. The results obtained from this study will be useful to design more potent CRTh2 antagonists.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.852-857
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• 2005

This paper discusses a human body extraction method for intelligent robot system. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. The temporal and gradient information is combined as hybrid silhouette. The motion region model is used to adjust combining parameters in hybrid silhouette. Finally, the experimental results show the superiority of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.23-31
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• 2000

Iterative curve evolution techniques are powerful methods for image segmentation. Classical methods proposed curve evolutions which guarantee close contours at convergence and, combined with the level set method, they easily handled curve topology changes. In this paper, we present a new geometric active contour model based on level set methods introduced by Osher & Sethian for detection of object boundaries or shape and we adopt anisotropic diffusion filtering method for removing noise from original image. Classical methods allow only one-way curve evolutions : shrinking or expanding of the curve. Thus, the initial curve must encircle all the objects to be segmented or several curves must be used, each one totally inside one object. But our method allows a two-way curve evolution : parts of the curve evolve in the outward direction while others evolve in the inward direction. It offers much more freedom in the initial curve position than with a classical geodesic search method. Our algorithm performs accurate and precise segmentations from noisy images with complex objects(jncluding sharp angles, deep concavities or holes), Besides it easily handled curve topology changes. In order to minimize the processing time, we use the narrow band method which allows us to perform calculations in the neighborhood of the contour and not in the whole image.

• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1117-1124
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• 2007

In this paper, an algorithm that can define the threshold value automatically proposed in order to detect a brain ventricle in MRI brain images. After the wavelet transform, edge sharpness, which means the average magnitude of detail signals on the contour of the object, was computed by using the magnitude of horizontal and vertical detail signals. The contours of a brain ventricle were detected by increasing the threshold value repeatedly and computing edge sharpness. When the edge sharpness became maximal, the optimal threshold was determined, and the detection of a brain ventricle was accomplished finally. In this paper, we compared the proposed algorithm with the geodesic active contour model numerically and verified the efficiency of the proposed algorithm by applying real MRI brain images.