• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.50-57
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• 2005

We present a simple and effective method of face and facial feature detection under pose variation of user face in complex background for the human-robot interaction. Our approach is a flexible method that can be performed in both color and gray facial image and is also feasible for detecting facial features in quasi real-time. Based on the characteristics of the intensity of neighborhood area of facial features, new directional template for facial feature is defined. From applying this template to input facial image, novel edge-like blob map (EBM) with multiple intensity strengths is constructed. Regardless of color information of input image, using this map and conditions for facial characteristics, we show that the locations of face and its features - i.e., two eyes and a mouth-can be successfully estimated. Without the information of facial area boundary, final candidate face region is determined by both obtained locations of facial features and weighted correlation values with standard facial templates. Experimental results from many color images and well-known gray level face database images authorize the usefulness of proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.580-584
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• 2011

Corner positioning templates are proposed in order to detect the accurate positions of corners that are extracted using 4-directional edge labeling. Top-down and bottom-up directional labeling are used to label the edge segments with four kinds of labels according to their directions. The points whose labels have changed are then determined as corners. The exact positions of the missing corners due to the disconnected edges are detected through the corner positioning templates that are determined according to the labels of start-points and end-points after the two-pass edge labeling. Experiment results show that the proposed method can detect the exact positions of the real corners.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.1-5
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• 2016

Most of systems engineers make a traceability matrix and attach it to their technical documents as a result of systems engineering activities. I have been working in the field of systems engineering for many years and have been watching traceability matrices created by systems engineers or developers from various companies. I have been thinking that some of them are not suitable in terms of purposes of traceability matrix. In this paper, I would like to suggest a right template for the traceability matrix in conformance to traceability purposes. The key is that traceability matrix should be created from higher level of requirements to current level of requirements.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1065-1068
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• 2003

The nano imprint process is one of the next generation lithography has been mentioned as one of major nanoreplication techniques because it is simple process, low cost, high replication fidelity and relatively high throughput. This process requires a surface contact between a template with patterns and a wafer on a stage. After contact, the vertical moving the template to the wafer causes some directional motions of the stage. Thus the stage must move according to the motions of the template to avoid the damage of the transferred patterns on the wafer. This study is to develop the wafer stage with a passive compliance to overcome the damage. This stage is designed with the concept like that it has a monolithic, symmetry and planar 6-DOF mechanism.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.250-255
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional 5$\times$5 gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether genuine or forged with more than 98% overall accuracy even without any knowledge of vaned freehand forgeries.

• ETRI Journal
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• v.32 no.5
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.592-603
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional $5\times{5}$ gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether it is genuine or forged with more than 98% overall accuracy even without any knowledge of varied freehand forgeries.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.945-948
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• 2000

The coupling properties of supermodes guided by grating-assisted directional couplers (GADCs) can be phrased in rigorous modal theory. Such a modal solution for TE modes expressed by simple electrical transmission-line networks is utilized to analyze the power distribution of GADCS with three guiding channels. In particular, the modal transmission-line theory can serve as a template for computational algorithms that systematically evaluate the coupling efficiency that are not readily obtained by other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.256-265
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• 2003

To improve reliability and practicality, a fingerprint-based biometric system needs to be robust to rotations of an input fingerprint and the processing speed should be fast. Accordingly, this paper presents a new filterbank-based fingerprint feature extraction and matching method that is robust to diverse rotations and reasonably fast. The proposed method fast extracts fingerprint features using a directional filter bank, which effectively decomposes an image into several subband outputs Since matching is also performed rapidly based on the Euclidean distance between the corresponding feature vectors, the overall processing speed is so fast. To make the system robust to rotations, the proposed method generates a set of feature vectors considering various rotations of an input fingerprint and then matches these feature vectors with the enrolled single template feature vector. Experimental results demonstrated the high speed of the proposed method in feature extraction and matching, along with a comparable verification accuracy to that of other leading techniques.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.