• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1318-1324
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• 2012

This paper proposes a novel method for Game character classification based on texture and edge orientation feature. The character dose not move(NPC) and move the character is classified. Classification of property within the character of straight line segments are used to extract features. First, the character inside edge feature extraction and then calculates EEDH, SSPD. The extracted attribute represents the energy of a particular direction. Thus, these properties were used to classify of NPC and Monster. The proposed method, the user can reduce the unnecessary time in the game.

• Current Optics and Photonics
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• v.2 no.4
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• pp.348-355
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• 2018

How to measure the creepage distance of an insulator quickly and accurately is a problem for the power industry at present, and the noticeable concern is that the high voltage insulation equipment cannot be measured online in the charged state. In view of this situation, we develop an on-line measurement system of creepage distance for high voltage insulators based on binocular stereo vision. We have proposed a method of generating linear structured light using a conical off-axis mirror. The feasibility and effect of two ways to solve the interference problem of strong sunlight have been discussed, one way is to use bandpass filters to enhance the contrast ratio of linear structured light in the images, and the other way is to process the images with adaptive threshold segmentation and feature point extraction. After the system is calibrated, we tested the measurement error of the on-line measurement system with a composite insulator sample. Experimental results show that the maximum relative error is 1.45% and the average relative error is 0.69%, which satisfies the task requirement of not more than 5% of the maximum relative error.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1183-1186
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• 2004

In the steel production line, the molten metal of a furnace is transformed into billet and then moves to the heating furnace of the hot rolling mill. This paper describes about the realtime billet characters recognition system in the steel production line. Normally, the billets are mixed at yard so that their identifications are very difficult and very important processing. The character recognition algorithm used in this paper is base on the subspace method by K-L transformation. With this method, we need no special feature extraction steps, which are usually error prone. So the gray character images are directly used as input vectors of the classifier. To train the classifier, we have extracted eigen vectors of each character used in the billet numbers, which consists of 10 arabia numbers and 26 alphabet aharacters, which are gathered from billet images of the production line. We have developed billet characters recognition system using this algorithm and tested this system in the steel production line during the 8-days. The recognition rate of our system in the field test has turned out to be 94.1% (98.6% if the corrupted characters are excluded). In the results, we confirmed that our recognition system has a good performance in the poor environments and ill-conditioned marking system like as steel production plant.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.266-274
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• 2003

Distance Fourier descriptors of local target boundary and feature information fusion using multiple MLPs (Multilayer perceptrons) are proposed. They are used to identify nonoccluded and partially occluded targets in natural FLIR (forward-looking infrared) images. After segmenting a target, radial Fourier descriptors as global shape features are defined from the target boundary. A target boundary is partitioned into four local boundaries to extract local shape features. In a local boundary, a distance function is defined from boundary points and a line between two extreme points. Distance Fourier descriptors as local shape features are defined by using distance function. One global feature vector and four local feature vectors are used as input data for multiple MLPs to determine final identification result of the target. In the experiments, we show that the proposed method is superior to the traditional feature sets with respect to the identification performance.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.852-859
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• 2009

Normally, to extract the defect in TFT-LCD inspection system, the image is obtained by using line scan camera or area scan camera which is achieved by CCD or CMOS sensor. Because of the limited dynamic range of CCD or CMOS sensor as well as the effect of the illumination, these images are frequently degraded and the important features are hard to decern by a human viewer. In order to overcome this problem, the feature vectors in the image are obtained by using the average intensity difference between defect and background based on the weber's law and the standard deviation of the background region. The defect detection method uses non-linear SVM (Supports Vector Machine) method using the extracted feature vectors. The experiment results show that the proposed method yields better performance of defect classification methods over conveniently method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.144-152
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• 2007

We propose a 3D modeling method for surface inspection of non-linear moving object. The laser lines reflect the surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. ill this paper, we use multi-line laser to make use of robust of single stripe method and high speed of single frame. Binarization and channel edge extraction method were used for robust laser line extraction. A new labeling method was used for laser line labeling. We acquired sink information between each 3D reconstructed frame by feature point matching, and registered each frame to one whole image. We verified the superiority of proposed method by applying it to container damage inspection system.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.15-21
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• 2007

We propose a 3D modeling method for surface inspection of non-constant velocity moving object. 1'lie laser lines reflect tile surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. In this paper, we use multi-line laser to improve the single stripe method and high speed of single frame. Binarization and edge extraction of frame image were proposed for robust laser each line extraction. A new labeling method was used for laser line labeling. We acquired some feature points for image matching from the frame data and juxtaposed the frames data to obtain a 3D shape image. We verified the superiority of proposed method by applying it to inspect container's damages.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.283-292
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• 2006

Interest about a latest security connection technology rises, and try to overcome security vulnerability Certification about on-line user methods through fingerprint that is biometries information apply. In this study, designs and implements fingerprint recognition system that is invariant to rotation by fingerprint recognition system for certification about on-line user. Proposed method focused in matching process through pre-process of fingerprint image, feature point extraction. Improved process time and correct recognition rate in fingerprint recognition system that is invariant to rotation presented in existing study. Also, improved noise, distortion problems that happen in preprocess of existing study applying directional Laplacian filter.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.506-511
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• 2004

Biometrics is getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry has been used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. Hence, it can be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. However, during experimentation, it was discovered that length measured from the tip of the finger was not a reliable feature. Hence, we propose a new technique based on Genetic Algorithm for extraction of the center of nail bottom, in order to use it for the length feature.