• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.67-75
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• 2013

Korea has developed coastal farming industry due to the environmental characteristics that its three sides are surrounded by sea. The damage of coastal farming industry caused by Asterias Amurensis with very strong reproductive rate and predaciousness has increased sharply every year. Moreover, Asterias Amurensis preys on living fish and shellfish and so the damage of fishermen is vern greater. In this paper, a method is proposed to extract effectively the features from the image of Asterias Amurensis acquired in the water. Because the proposed method extracts convex features using 6-directional scanning, it selects a fewer number of feature candidates than the conventional one. In addition, after selecting candidate concave points using the extracted convex features and centers of region, the final concave features are extracted. Due to the features of the starfish which lives in groups, individuals of the starfish in the input image are concentrated. Thus, it is significant to minimize the number of feature candidates extracted from the input image. The experimental results indicate an improvement of the proposed feature extraction method over the conventional one as evidenced by the fact that the feature extract was 88 % of the feature candidates.

• 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 the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.136-142
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• 2007

Recent researches in the recognition system have shown that SVM (Support Vector Machine) classifiers often have superior recognition rates in comparison to other classifiers. In this paper, we present the handwritten numeral recognition algorithm using SVM classifiers. The numeral features used in our algorithm are mesh features, directional features by Kirsch operators and concavity features, where first two features represent the foreground information of numerals and the last feature represents the background information of numerals. These features are complements each of the other. Since SVM is basically a binary classifier, it is required to construct and combine several binary SVMs to get the multi-class classifiers. We use two strategies for implementing multi-class SVM classifiers: "one against one" and "one against the rest", and examine their performances on the features used. The efficiency of our method is tested by the CENPARMI handwritten numeral database, and the recognition rate of 98.45% is achieved.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.89-101
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• 2014

In this paper, we proposed a new local micro pattern, Signed Local Directional Pattern(SLDP). SLDP uses information of edges to represent the face's texture. This can produce a more discriminating and efficient code than other state-of-the-art methods. Each micro pattern of SLDP is encoded by sign and its major directions in which maximum edge responses exist-which allows it to distinguish among similar edge patterns that have different intensity transitions. In this paper, we divide the face image into several regions, each of which is used to calculate the distributions of the SLDP codes. Each distribution represents features of the region and these features are concatenated into a feature vector. We carried out facial expression recognition with feature vectors and SVM(Support Vector Machine) on Cohn-Kanade and JAFFE databases. SLDP shows better classification accuracy than other existing methods.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.115-125
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• 2011

Manufacturing companies usually manage the process to achieve high quality using various types of control chart in statistical process control. When an assignable cause occurs in a process, the data in the control chart changes with different patterns by the specific causes. It is important in process control to classify the CCP (Control Chart Pattern) recognition for fast decision making. In former research, gathered data from process used to apply as raw data, leads to degrade the performance of recognizer and to decrease the learning speed. Therefore, feature based recognizer, employing feature extraction method, has been studied to enhance the classification accuracy and to reduce the dimension of data. We propose the method to extract features that take the distances between CCP data and reference vector generated from BDK (Bi-Directional Kohonen Network). We utilize those features as the input vectors in ANN (Artificial Neural Network) and compare with raw data applied ANN to evaluate the performance.

• Convergence Security Journal
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• v.6 no.3
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• pp.29-35
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• 2006

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Convergence Security Journal
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• v.7 no.3
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• pp.39-44
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• 2007

In order to detect and locate edge features precisely in real images we have developed an algorithm by introducing a nonlocal differentiation of intensity profiles called adaptive directional derivative (ADD), which is evaluated independently of varying ramp widths. In this paper, we first develop the edge detector system employing the ADD and then, the performance of the algorithm is illustrated by comparing the results to those from the Canny's edge detector.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.309-312
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• 2000

In this work, a new algorithm for canceling MRI artifact due to translational motion in image plane is described. In the previous approach, the motions in the x direction and the y direction are estimated simultaneously. By analyzing their features, each x and y directional motion is canceled by different algorithms in two steps. First, it is noticed that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal. Next, the y directional motion is canceled by using a new constraint condition. This algorithm is shown to be effective by using a phantom image with simulated motion.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.731-740
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• 2010

A region merging technique is suggested in this paper for the segmentation of high-spatial resolution imagery. It employs a region growing scheme based on the region adjacency graph (RAG). The proposed algorithm uses directional neighbor-line average feature vectors to improve the quality of segmentation. The feature vector consists of 9 components which includes an observation and 8 directional averages. Each directional average is the average of the pixel values along the neighbor line for a given neighbor line length at each direction. The merging coefficients of the segmentation process use a part of the feature components according to a given merging coefficient order. This study performed the extensive experiments using simulation data and a real high-spatial resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for the object-based analysis of high-spatial resolution images.

• ETRI Journal
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• v.34 no.1
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• pp.24-34
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• 2012

In this paper, the directional carrier sense multiple access/collision avoidance (CSMA/CA) protocol in the immediate acknowledgement mode for IEEE 802.15.3c is analyzed under saturation environments. For the analysis, a sensing region and an exclusive region with a directional antenna are computed probabilistically and a Markov chain model in which the features of IEEE 802.15.3c and the effects of using directional antennas are incorporated is analyzed. An algorithm to find the maximal number of concurrently transmittable frames is proposed. The system throughput and the average transmission delay are obtained in closed forms. The numerical results show the impact of directional antennas on the CSMA/CA media access control (MAC) protocol. For instance, the throughput with a small beamwidth of antenna is more than ten times larger than that for an omnidirectional antenna. The overall analysis is verified by a simulation. The obtained results will be helpful in developing an MAC protocol for enhancing the performance of mmWave wireless personal area networks.