• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.533-542
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• 2008

Background subtraction from video data is one of the most important task in various realtime machine vision applications. In this paper, a new scheme for background subtraction based on the hexagonal pixel sampling is proposed. Generally it has been found that hexagonal spatial sampling yields smaller quantization errors and remarkably improves the understanding of connectivity. We try to apply the hexagonally sampled image to the LBP based non-parametric background subtraction algorithm. Our scheme makes it possible to omit the bilinear pixel interpolation step during the local binary pattern generation process, and, consequently, can reduce the computation time. Experimental results revealed that our approach based on hexagonal spatial sampling is very efficient and can be utilized in various background subtraction applications.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.141-149
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• 2023

Repacked mobile apps constitute about 78% of all malware of Android, and it greatly affects the technical ecosystem of Android. Although many methods exist for repacked app detection, most of them suffer from performance issues. In this manuscript, a novel method using the Constant Key Point Selection and Limited Binary Pattern (CKPS: LBP) Feature extraction-based Hashing is proposed for the identification of repacked android applications through the visual similarity, which is a notable feature of repacked applications. The results from the experiment prove that the proposed method can effectively detect the apps that are similar visually even that are even under the double fold content manipulations. From the experimental analysis, it proved that the proposed CKPS: LBP method has a better efficiency of detecting 1354 similar applications from a repository of 95124 applications and also the computational time was 0.91 seconds within which a user could get the decision of whether the app repacked. The overall efficiency of the proposed algorithm is 41% greater than the average of other methods, and the time complexity is found to have been reduced by 31%. The collision probability of the Hashes was 41% better than the average value of the other state of the art methods.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.73-79
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• 2009

In this paper, a method is proposed that enhances the performance of the facial expression recognition using template matching of Local Binary Pattern(LBP) histogram. In this method, the face image is segmented into blocks, and the LBP histogram is constructed to be used as the feature of the block. Block dissimilarity is calculated between a block of input image and the corresponding block of the model image. Image dissimilarity is defined as the weighted sum of the block dissimilarities. In conventional methods, the block weights are assigned by intuition. In this paper a new method is proposed that optimizes the weights from training samples. An experiment shows the recognition rate is enhanced by the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.9-17
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• 2004

We present a performance improvement of Binary CDMA by flattening the correlation values. A Binary CDMA system, in which multi-leveled transmission signal of multi-code CDMA is clipped into a binary value, is cost-efficient since the strict linearity of the power amplifier is relieved. However, a loss of orthogonality among user channels due to the clipping causes the correlation values at the receiver to have a random distribution. If the correlation value for even a single channel goes too low, the average BER drops considerably. We developed a method of correlation flattening, where the binary chip pattern at the transmitter is adjusted so that the correlation values have averaged magnitude. Experimental results on several spreading codes show that the correlation flattening method increases the number of available channels at reduced BER.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.362-367
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• 2018

A complementary metal oxide semiconductor (CMOS) binary image sensor is proposed for low-power and low-noise operation. The proposed binary image sensor has the advantages of reduced power consumption and fixed pattern noise (FPN). A gate/body-tied (GBT) p-channel metal-oxide-semiconductor field-effect transistor (PMOSFET)-type photodetector is used as the proposed CMOS binary image sensor. The GBT PMOSFET-type photodetector has a floating gate that amplifies the photocurrent generated by incident light. Therefore, the sensitivity of the GBT PMOSFET-type photodetector is higher than that of other photodetectors. The proposed CMOS binary image sensor consists of a pixel array with $394(H){\times}250(V)$ pixels, scanners, bias circuits, and column parallel readout circuits for binary image processing. The proposed CMOS binary image sensor was analyzed by simulation. Using the dynamic comparator, a power consumption reduction of approximately 99.7% was achieved, and this performance was verified by the simulation by comparing the results with those of a two-stage comparator. Also, it was confirmed using simulation that the FPN of the proposed CMOS binary image sensor was successfully reduced by use of the double sampling process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.576-586
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• 1996

Original binary image can be reconstructed by morphological bymorphological skeleton(MS) image. And then, the information of MS image points can be applied to a pattern recognition andimage communication. But if we apply MS to a pattern recognition and image communication, there are two problems. That is to say, binary MS processing times is long and skeleton points of MS are high redundancy. And then, to solve these problems, this paper proposes DGMS. After simulating by the proposed method to $256{\times}256$ binary image which is GIRL, we reduce processing time and skeleton points about 1.5~6.5% comparing with the result of GMS method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.163-164
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• 2015

In order to decode the bar code image binarization process is indispensable. The traditional binarization method is a global threshold binarization and local threshold binarization. Global threshold binarization method using a single threshold. In some cases there is a blur, or if the brightness is different from the bar code image. Therefore, binary pattern information is not retained. Local threshold method is binaized pattern information is maintained but processing speed is slow than global threshold binarization. The algorithm for solving this problem, there is modified binary algorithm. In this paper, we proposed hardware IP implemented by Vivado of modified binary algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.272-287
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• 2017

This paper proposes new methods, named Derivative Code (DerivativeCode) and Derivative Code Pattern (DCP), for object recognition. The discriminative derivative code is used to capture the local relationship in the input image by concatenating binary results of the mathematical derivative value. Gabor based DerivativeCode is directly used to solve the palmprint recognition problem, which achieves a much better performance than the state-of-art results on the PolyU palmprint database. A new local pattern method, named Derivative Code Pattern (DCP), is further introduced to calculate the local pattern feature based on Dervativecode for object recognition. Similar to local binary pattern (LBP), DCP can be further combined with Gabor features and modeled by spatial histogram. To evaluate the performance of DCP and Gabor-DCP, we test them on the FERET and PolyU infrared face databases, and experimental results show that the proposed method achieves a better result than LBP and some state-of-the-arts.

• Journal of the Korean Chemical Society
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• v.59 no.5
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• pp.423-428
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• 2015

(1S)-(+)-10-camphorsulfonic acid (CSA) and HCl were used together as a binary dopant in the electrodeposition of polyaniline (PAni). (+)-CSA and HCl were added in different mole ratios (9:1 and 6:4). (+)-CSA-doped and binary-doped PAni exhibited markedly different ultraviolet-visible and circular dichroism spectral characteristics due to differences in their conformations. Distinct helical structures are observed in the scanning electron microscopy images of (+)-CSA-doped PAni. The X-ray diffraction pattern of (+)-CSA-doped PAni exhibited remarkably higher crystallinity than that of HCl-doped PAni which is associated with the helical ordering along the polymer chains. The conformational changes due to the binary doping in chiral PAni had a significant effect on its chiroptical and electrochemical properties, morphology, and crystallinity, thus determined its conductivity.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.58-69
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.