• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3236-3238
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• 1999

This paper proposes a new face recognition technique in the dynamic link architecture which shows robustness against size variation and distortion. The face recognition technique in the dynamic link architecture so far was not appropriate for the recognition of various size of faces because of the fixed size of the graph and the fixed value of a of the Gabor filter not considering the size of the face. The proposed face recognition algorithm can represent the input facial image by a suitable size of labeled graph, and it can also adjust the dilation width and the height of the vibrating amplitude of the Gabor filter, thus face recognition in the dynamic link architecture is even applicable regardless of the size of the face.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.439-445
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• 2021

Low-cost, ultra-high-speed cameras, made possible by the development of image sensors and small displays, can be very useful in image processing and pattern recognition. This paper introduces an algorithm that corrects irregular lighting from a high-speed image that is continuously input with a slight time interval, and which then obtains an exposed skin color region that is the area of interest in a person from the corrected image. In this study, the non-uniform lighting effect from a received high-speed image is first corrected using a frame blending technique. Then, the region of interest is robustly obtained from the input high-speed color image by applying an elliptical skin color distribution model generated from iterative learning in advance. Experimental results show that the approach presented in this paper corrects illumination in various types of color images, and then accurately acquires the region of interest. The algorithm proposed in this study is expected to be useful in various types of practical applications related to image recognition, such as face recognition and tracking, lighting correction, and video indexing and retrieval.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1349-1355
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• 1999

A power distribution facility map is drawn on cadastral map. Besides, grid lines are added on the map for sectionalization. For automatic recognition of the map, we first extract recognizing regions. In this paper, we propose an extraction method of recognizing regions by partially extending thinned image. The proposed method is consist of three phases, binarization phase, thinning phase and partial extending phase. The first phase generate a binary image using threshold value which is obtained by histogram analysis. The binary image contains many part of recognizing regions, but not all. The second phase generate thinned image which is generated by appling thinning operator to the binary image. And the third phase extends thinned image from terminal point until satisfying termination condition. The proposed method is tested on several power distribution facility maps, and the results are presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.50-57
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• 1992

Neural networks have become more popular recently and are now being applied to numerous fiedls. One of the major applications of neural networks is image recognition. Various image recognition system have been proposed so far, but there is no definite solution yet. In this paper, we propose a design of Fuzzy Neural Network Image Recognizer(FNNIR). Our model uses a fuzzy neural network model, named SONN[KIM90]. This model returns the information of the number of clusters and cluster and cluster center values for a given image data ste. Unlike the well-kinwn backpropagation technique, we do not need retraining for new data. Our newly designed image recongitionsystem FNNIR that uses fuzzy merger is proposed and experimented for a sample color image.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.231-234
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• 2001

This paper proposes a face recognition technique that effectively combines elastic graph matching (EGM) and Fisherface algorithm. EGM as one of dynamic lint architecture uses not only face-shape but also the gray information of image, and Fisherface algorithm as a class specific method is robust about variations such as lighting direction and facial expression. In the proposed face recognition adopting the above two methods, the linear projection per node of an image graph reduces dimensionality of labeled graph vector and provides a feature space to be used effectively for the classification. In comparison with a conventional method, the proposed approach could obtain satisfactory results in the perspectives of recognition rates and speeds. Especially, we could get maximum recognition rate of 99.3% by leaving-one-out method for the experiments with the Yale Face Databases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.54-62
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• 2018

According to evolution of technologies, many devices related to various applications were researched. The advanced driver assistance system is a famous technique effected from the evolution. The technique of driver assistance uses image recognition methods to collect exactly information around the vehicle. The computing power of driver assistance device has become more improved than in the past. However, it's difficult that processed various recognition methods at real-time. We propose new frame skip method to process various recognition methods at real-time in the limited hardware. In the previous researches, frame skip rate was set up static values, thus the number of processed frames through recognition methods was smaller. We set up the frame skip rate dynamically using a driving condition of vehicle through speed and acceleration value, in addition, the number of processed frames was maximized. The performance is improved more 32.5% than static frame skip method.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.459-464
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• 2003

This paper proposes the use of a wavelet based image transform algorithm in human iris recognition method and the effectiveness of this technique will be determined in preprocessing of extracting Iris image from the user´s eye obtained by imaging device such as CCD Camera or due to torsional rotation of the eye, and it also resolves the problem caused by invariant under translations and dilations due to tilt of the head. This technique values through the proposed translation-invariant wavelet transform algorithm rather than the conventional wavelet transform method. Therefore we extracted the best-matching iris feature values and compared the stored feature codes with the incoming data to identify the user. As result of our experimentation, this technique demonstrate the significant advantage over verification when it compares with other general types of wavelet algorithm in the measure of FAR & FRR.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.125-130
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• 2016

Automatic quality inspection by computer vision can be applied and give a solution to the pharmaceutical industry field. Pharmaceutical capsule can be easily affected by flaws like dents, cracks, holes, etc. In order to solve the quality inspection problem, it is required computationally efficient image processing technique like thresholding, boundary edge detection and segmentation and some automated systems are available but they are very expensive to use. In this paper, we have developed a dented capsule image processing technique using edge-based image segmentation, TLS(Total Least Squares) curve fitting technique and adopted low cost camera module for capsule image capturing. We have tested and evaluated the accuracy, training and testing time of the classification recognition algorithms like PCA(Principal Component Analysis), ICA(Independent Component Analysis) and SVM(Support Vector Machine) to show the performance. With the result, PCA, ICA has low accuracy, but SVM has good accuracy to use for classifying the dented capsule.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1836-1839
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• 1997

This paper presents machine vision technique with a camera modeling that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering, that is, the optical centers of lens elements are not strictly collinear. It is our purpose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing.