• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.316-320
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• 2016

In this paper, we presents a pattern recognition by considering the spatial co-occurrence among micro-patterns of texture images. The micro-patterns of texture image have been extracted by local binary pattern based on median(MLBP) of block image, and the recognition process is based on co-occurrence among MLBPs. The MLBP is applied not only to consider the local character but also analyze the pattern in order to be robust noise, and spatial co-occurrence is also applied to improve the recognition performance by considering the global space of image. The proposed method has been applied to recognized 17 RGB images of 120*120 pixels from Mayang texture image based on Euclidean distance. The experimental results show that the proposed method has a texture recognition performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.588-591
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• 2009

This paper proposes a reversible information hiding method for binary images. A half of pixels in noisy blocks on cover images is candidate for embeddable pixels. Among the candidate pixels, we select compressive pixels by bit patterns of its neighborhood to compress the pixels effectively. Thus, embeddable pixels in the proposed method are compressive pixels in noisy blocks. We provide experimental results using several binary images binarized by the different methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.11
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• pp.901-907
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• 2000

As the minimum feature size for making ULSI approaches the wavelength of light source in optical lithography, the aerial image is so hardly distorted because of the optical proximity effect that the accurate mask image reconstruction on wafer surface is almost impossible. We applied the Optical Proximity Correction(OPC) on isolated patterns assuming Attenuated Phase Shift Mask(APSM) as well as binary mask, to correct the widening of isolated patterns. In this study, we found that applying OPC to APSM shows much better improvement not only in enhancing the resolution and fidelity of t도 images but also in enhancing the process margin than applying OPC to the binary mask. Also, we propose the OPC method of APSM for isolated patterns, the size of which is less than the wavelength of the ArF excimer laser. Finally, we predicted the resolution limit of optical lithography through the aerial image simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.726-736
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• 1997

The textual image compression by pattern matching is a coding scheme that exploits the correlations between patterns. When we compress the Hangul (Korean character) text by patern matching, the collerations between patterns may decrease due to randoem contacts between phonemes. Therefore in this paper we separate connected phonemes to exploit effectively the corrlation between patterns by inducting the amtch. In the process of sequation, we decide whether the patterns have vowel component or not, and then vowels connected with consonant ae separated. When we compare the proposed algorithm with the existing algorith, the compression ratio is increased by 1.3%-3.0% than PMS[5] in lossy mode, by 3.4%-9.1% in lossless mode than that of SPM[7] which is submitted to standard committe for second generation binary compression algorithm.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.4869-4873
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• 2016

Colonoscopy is currently the best technique available for the detection of colon cancer or colorectal polyps or other precursor lesions. Computer aided detection (CAD) is based on very complex pattern recognition. Local binary patterns (LBPs) are strong illumination invariant texture primitives. Histograms of binary patterns computed across regions are used to describe textures. Every pixel is contrasted relative to gray levels of neighbourhood pixels. In this study, colorectal polyp detection was performed with colonoscopy video frames, with classification via J48 and Fuzzy. Features such as color, discrete cosine transform (DCT) and LBP were used in confirming the superiority of the proposed method in colorectal polyp detection. The performance was better than with other current methods.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.9
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• pp.64-71
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• 1994

In this study, optimizing BPOFs are encoded by Simulated Annealing algorithm that is widely used among the optimization algorithms. Two BPOFs are trained by digit patterns, 0~9, and the digits each having 4 intraclass patterns are multiplexed. When each digit is encoded by four bit binary code, from the results of computer simulation, the correlation pezk is shown at binary value 1 position among the spatially separated four positions at the correlation plane And then, the designed BPOFs are implemented by CGH technique. Through the optical correlation experiment, satisactory results are achieved, inspite of some experimental errors and information loss owing to the amplitude type CGH filter.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1610-1620
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• 2010

This paper proposes a motion-adaptive 3-D deinterlacing algorithm based on an adaptive-thresholded motion detection and an interpolation method using binary patterns to compensate motion missing and false motion errors. For efficient motion detection, we adaptively decided a threshold value according to the complexity of image. Many edge-based interpolation algorithms have been proposed to improve the subjective quality. Recently, to efficiently interpolate low angle edge and line, a method using predefined binary patterns has been proposed. In this paper, we propose an improved method by modifying the binary patterns. Simulation results have shown that the proposed method provides better performance than the existing methods.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.468-488
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• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• Proceedings of the Optical Society of Korea Conference
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• 2001.02a
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• pp.62-63
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• 2001

We studied a method to use a variable discrete random phase mask in 2-D binary data representation for efficient holographic data storage. The variable phase mask is realized by use of a liquid crystal display.