• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3165-3177
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• 1999

With the recent outstanding advance in computer software and hardware, a number of researches to enhance the manufacturing speed and the process accuracy has been undertaken in many fields of textile industry. Frequently issued problems of automatic recognition of textile wrinkles in a grey scale image are as follows. First, changes in grey level intensity of wrinkles are so minute. Second, as both colors and patterns in a grey scale image appear in grey level intensity, it is difficult to sort out the wrinkle information only. Third, it is also difficult to distinguish grey level intensity changed by wrinkles from those by uneven illumination. This paper suggests a method of automatic recognition of textile wrinkles that can solve above problems concerned with wrinkles, which can be raised in a manufacturing process as one of errors. In this paper, we first make the outline of wrinkles distinctly, apply the block matching algorithm used in motion estimation, and then estimate block locations of target images corresponding to blocks of standard images with the assumption that wrinkles are kind of textile distortions caused by directional forces. We plot a "wrinkle map" considering distances between wrinkles as depths of wrinkles. But because mismatch can occur by different illumination intensity and changes in tensions and directions of the force, there are also undesirable patterns in the map. Post processing is needed to filter them out and get wrinkles information only. We use average grey level intensity of wrinkle map to recognize wrinkles. When it comes to textile with colors and patterns, previous researches on wrinkles in grey scale image hasn't been successful. But we make it possible by considering wrinkles as distortion.istortion.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.206-213
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• 2015

An omni-directional, graded-index and textured ZnO nanorods with $MgF_2$ anti-reflective(AR) coating films for the electro optical tracking system(EOTS) by e-beam evaporation method are presented. we achieved that the graded index structure can minimize image tracking interference of EOTS which is comparable to a general AR coating films. Optimized ZnO nanorods with $MgF_2$ AR coating films lead to decreasing Fresnel reflection by gradient refractive index. According to our experiment results, ZnO nanorods with $MgF_2$ AR coating films can be used for various electro optical system to improve the optical performance.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.1
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• pp.21-28
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• 2000

Although commercial PIV systems have been widely used for the non-intrusive velocity field measurement of fluid flows, they are still under development and have considerable room for improvement. In this study, a single-frame double-exposure PIV system using a high-resolution CCD camera was developed. A pulsed Nd:Yag laser and high-resolution CCD camera were synchronized by a home-made control circuit. In order to resolve the directional ambiguity problem encountered in the single-frame PIV technique, the second particle image was genuinely shifted in the CCD sensor array during the time interval dt. The velocity vector field was determined by calculating the displacement vector at each interrogation window using cross-correlation with 50% overlapping. In order to check the effect of spatial resolution of CCD camera on the accuracy of PIV velocity field measurement, the developed PIV system with three different resolution modes of the CCD camera (512 ${\times}$ 512, lK ${\times}$ IK, 2K ${\times}$ 2K) was applied to a turbulent flow which simulate the Zn plating process of a steel strip. The experimental model consists of a snout and a moving belt. Aluminum flakes about $1{\mu}m$ diameter were used as scattering particles for the liquid flow in the zinc pot and the gas flow above the zinc surface was seeded with atomized olive oil with an average diameter of 1-$3{\mu}m$. Velocity field measurements were carried out at the strip speed $V_s$=1.0 m/s. The 2K ${\times}$ 2K high-resolution PIV technique was significantly superior compared to the smaller pixel resolution PIV system. For the cases of 512 ${\times}$ 512 and 1K ${\times}$ 1K pixel resolution PIV system, it was difficult to get accurate flow structure of viscous flow near the wall and small vortex structure in the region of large velocity gradient.

• 전자공학회논문지 IE
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• v.44 no.2
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• pp.32-40
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• 2007

In this paper, the crease extraction method is proposed to improve the accuracy of feature extraction within the fingerprint image. First of all, for each pixel in fingerprint image, it calculates the average grey level and variance to determine if the current pixel composes the crease, and estimates the direction of crease. Secondly, once the direction of every pixel in crease candidate area is estimated, it is decomposed into 8 different images, depending on their direction. The properties of crease consists of the length of the crease candidate area, the correspondence between the crease direction and the pixel distribution direction, the difference between the ridge direction and the pixel distribution direction, and finally the grey level of the candidate pixels. The proposed method finally extracts the crease from the crease clusters estimated from directional images. In conclusion, applying the proposed method improved the accuracy of overall feature extraction by 91.4% by accurately and precisely extracting the crease from fingerprint image.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.80-88
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• 2006

In this paper we developed a novel system for automatic detection of mass type breast cancer on dense digital mammogram images. The new approaches presented in this paper are as follows: 1) we presented a method that stably decides the mass center and radius without being affected by image signal irregularity. 2) We developed a radial directional filter that is suitable to process mass image signal. 3) And we developed the multiple feature function based on mass shape spiculation, mass center homogeneity, and mass eccentricity, so as to determine mass-type breast cancer. When the proposed system is applied to dense mammographic images, the true 기arm rate is improved by 10% over a conventional system while the false alarm is increased by 1 per image.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1033-1039
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• 2012

In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.277-286
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• 2014

In this paper, we propose a texture feature-based language identification by fusion of Gabor, MDLC (multi-lag directional local correlation), and co-occurrence features. In the proposed method, for a test image, Gabor magnitude images are first obtained by Gabor transform followed by magnitude operator. Moments for the Gabor magniude images are then computed and vectorized. MDLC images are then obtained by MDLC operator and their moments are computed and vectorized. GLCM (gray-level co-occurrence matrix) is next calculated from the test image and co-occurrence features are computed using the GLCM, and the features are also vectorized. The three vectors of the Gabor, MDLC, and co-occurrence features are fused into a feature vector. In classification, the WPCA (whitened principal component analysis) classifier, which is usually adopted in the face identification, searches the training feature vector most similar to the test feature vector. We evaluate the performance of our method by examining averaged identification rates for a test document image DB obtained by scanning of documents with 15 languages. Experimental results show that the proposed method yields excellent language identification with rather low feature dimension for the test DB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2277-2282
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• 2009

In this paper, we proposed a new recognition method can be used in application systems using morphological features, difference operators and ART2 algorithm. At first, edges are extracted from an acquired car image by a camera using difference operators and the image of extracted edges is binarized by a block binarization method. In order to extract license plate area, noise areas are eliminated by applying morphological features of new and existing types of license plate to the 8-directional edge tracking algorithm in the binarized image. After the extraction of license plate area, mean binarization and mini-max binarization methods are applied to the extracted license plate area in order to eliminated noises by morphological features of individual elements in the license plate area, and then each character is extracted and combined by Labeling algorithm. The extracted and combined characters(letter and number symbols) are recognized after the learning by ART2 algorithm. In order to evaluate the extraction and recognition performances of the proposed method, 200 vehicle license plate images (100 for green type and 100 for white type) are used for experiment, and the experimental results show the proposed method is effective.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.52-61
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• 2006

Orthogonal wavelet tansform which is generally used in image and signal processing applications has limited performance because of lack of shift invariance and low directional selectivity. To overcome these demerits complex wavelet transform has been proposed. In this paper, we present an efficient image denoising method using dual-tree complex wavelet transform and Bernoulli-Gauss prior model. In estimating hyper-parameters for Bernoulli-Gaussian model, we present two simple and non-iterative methods. We use hypothesis-testing technique in order to estimate the mixing parameter, Bernoulli random variable. Based on the estimated mixing parameter, variance for clean signal is obtained by using maximum generalized marginal likelihood (MGML) estimator. We simulate our denoising method using dual-tree complex wavelet and compare our algorithm to well blown denoising schemes. Experimental results show that the proposed method can generate good denoising results for high frequency image with low computational cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.860-867
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• 2003

In this paper, an efficient core point detection method using orientation pattern labeling is proposed in fingerprint image. The core point, which is one of the singular points in fingerprint image, is used as the reference point in the most fingerprint recognizing system. Therefore, the detection of the core point is the most essential step of the fingerprint recognizing system, it can affect in the whole system performance. The proposed method could detect the position of the core point by applying the labeling method for the directional pattern which is come from the distribution of the ridges in fingerprint image and applying detailed algorithms for the decision of the core point's position. The simulation result of proposed method is better than the result of Poincare index method and the sine map method in executing time and detecting rate. Especially, the Poincare index method can't detect the core point in the detection of the arch type and the sine map method takes too much times for executing. But the proposed method can overcome these problems.