• Title/Summary/Keyword: Binary mask

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Learning Directional LBP Features and Discriminative Feature Regions for Facial Expression Recognition (얼굴 표정 인식을 위한 방향성 LBP 특징과 분별 영역 학습)

  • Kang, Hyunwoo;Lim, Kil-Taek;Won, Chulho
    • Journal of Korea Multimedia Society
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    • v.20 no.5
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    • pp.748-757
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    • 2017
  • In order to recognize the facial expressions, good features that can express the facial expressions are essential. It is also essential to find the characteristic areas where facial expressions appear discriminatively. In this study, we propose a directional LBP feature for facial expression recognition and a method of finding directional LBP operation and feature region for facial expression classification. The proposed directional LBP features to characterize facial fine micro-patterns are defined by LBP operation factors (direction and size of operation mask) and feature regions through AdaBoost learning. The facial expression classifier is implemented as a SVM classifier based on learned discriminant region and directional LBP operation factors. In order to verify the validity of the proposed method, facial expression recognition performance was measured in terms of accuracy, sensitivity, and specificity. Experimental results show that the proposed directional LBP and its learning method are useful for facial expression recognition.

EXTRACTION OF THE LEAN TISSUE BOUNDARY OF A BEEF CARCASS

  • Lee, C. H.;H. Hwang
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2000.11c
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    • pp.715-721
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    • 2000
  • In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

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Bar Code Location Algorithm Using Pixel Gradient and Labeling (화소의 기울기와 레이블링을 이용한 효율적인 바코드 검출 알고리즘)

  • Kim, Seung-Jin;Jung, Yoon-Su;Kim, Bong-Seok;Won, Jong-Un;Won, Chul-Ho;Cho, Jin-Ho;Lee, Kuhn-Il
    • The KIPS Transactions:PartD
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    • v.10D no.7
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    • pp.1171-1176
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    • 2003
  • In this paper, we propose an effective bar code detection algorithm using the feature analysis and the labeling. After computing the direction of pixels using four line operators, we obtain the histogram about the direction of pixels by a block unit. We calculate the difference between the maximum value and the minimum value of the histogram and consider the block that have the largest difference value as the block of the bar code region. We get the line passing by the bar code region with the selected block but detect blocks of interest to get the more accurate line. The largest difference value is used to decide the threshold value to obtain the binary image. After obtaining a binary image, we do the labeling about the binary image. Therefore, we find blocks of interest in the bar code region. We calculate the gradient and the center of the bar code with blocks of interest, and then get the line passing by the bar code and detect the bar code. As we obtain the gray level of the line passing by the bar code, we grasp the information of the bar code.

Optical Image Encryption Based on Characteristics of Square Law Detector (세기검출기를 이용한 광 영상 암호화)

  • Lee, Eung-Dae;Park, Se-Jun;Lee, Ha-Un;Kim, Su-Jung
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.39 no.3
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    • pp.34-40
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    • 2002
  • In this paper, a new encryption method for a binary image using Phase modulation and Fourier transform is proposed. For decryption we use the characteristics of square law detector. In encryption process, a key image is obtained by phase modulation of 256 level random pattern and its Fourier transformation, and input image is encrypted by Fourier transforming the multiplication of the phase modulated random pattern and phase modulated input image. The encrypted image and key image have only phase information, so they can not be copied or counterfeited and the original image can not be decrypted without the key image. To reconstruct the original image, each phase mask of the key image and the encrypted image must be placed on each path of the Mach-Zehnder interferometry with Fourier transform lens and the output image is obtained in the form of intensity in the CCD(Charge Coupled Device) camera. The real-time decryption is possible in the proposed system by use of a LCD as a phase modulator and a CCD camera as an intensity detector. The proposed method shows a good performance in the computer simulation and optical experiment as an encryption scheme.

Obtaining Object by Using Optimal Threshold for Saliency Map Thresholding (Saliency Map을 이용한 최적 임계값 기반의 객체 추출)

  • Hai, Nguyen Cao Truong;Kim, Do-Yeon;Park, Hyuk-Ro
    • The Journal of the Korea Contents Association
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    • v.11 no.6
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    • pp.18-25
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    • 2011
  • Salient object attracts more and more attention from researchers due to its important role in many fields of multimedia processing like tracking, segmentation, adaptive compression, and content-base image retrieval. Usually, a saliency map is binarized into black and white map, which is considered as the binary mask of the salient object in the image. Still, the threshold is heuristically chosen or parametrically controlled. This paper suggests using the global optimal threshold to perform saliency map thresholding. This work also considers the usage of multi-level optimal thresholds and the local adaptive thresholds in the experiments. These experimental results show that using global optimal threshold method is better than parametric controlled or local adaptive threshold method.

3-D Object Tracking using 3-D Information and Optical Correlator in the Stereo Vision System (스테레오 비젼 시스템에서 3차원정보와 광 상관기를 이용한 3차원 물체추적 방법)

  • 서춘원;이승현;김은수
    • Journal of Broadcast Engineering
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    • v.7 no.3
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    • pp.248-261
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    • 2002
  • In this paper, we proposed a new 3-dimensional(3-D) object-tracking algorithm that can control a stereo camera using a variable window mask supported by which uses ,B-D information and an optical BPEJTC. Hence, three-dimensional information characteristics of a stereo vision system, distance information from the stereo camera to the tracking object. can be easily acquired through the elements of a stereo vision system. and with this information, we can extract an area of the tracking object by varying window masks. This extractive area of the tracking object is used as the next updated reference image. furthermore, by carrying out an optical BPEJTC between a reference image and a stereo input image the coordinates of the tracking objects location can be acquired, and with this value a 3-D object tracking can be accomplished through manipulation of the convergence angie and a pan/tilt of a stereo camera. From the experimental results, the proposed algorithm was found to be able to the execute 3-D object tracking by extracting the area of the target object from an input image that is independent of the background noise in the stereo input image. Moreover a possible implementation of a 3-D tele-working or an adaptive 3-D object tracker, using the proposed algorithm is suggested.

Enhanced ART1 Algorithm for the Recognition of Student Identification Cards of the Educational Matters Administration System on the Web (웹 환경 학사관리 시스템의 학생증 인식을 위한 개선된 ART1 알고리즘)

  • Park Hyun-Jung;Kim Kwang-Baek
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.5 s.37
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    • pp.333-342
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    • 2005
  • This paper proposes a method, which recognizes student's identification card by using image processing and recognition technology and can manage student information on the web. The presented scheme sets up an average brightness as a threshold, based on the brightest Pixel and the least bright one for the source image of the ID card. It is converting to binary image, applies a horizontal histogram, and extracts student number through its location. And, it removes the noise of the student number region by the mode smoothing with 3$\times$3 mask. After removing noise from the student number region, each number is extracted using vertical histogram and normalized. Using the enhanced ART1 algorithm recognized the extracted student number region. In this study, we propose the enhanced ART1 algorithm different from the conventional ART1 algorithm by the dynamical establishment of the vigilance parameter. which shows a tolerance limit of unbalance between voluntary and stored patterns for clustering. The Experiment results showed that the recognition rate of the proposed ART1 algorithm was improved much more than that of the conventional ART1 algorithm. So, we develop an educational matters administration system by using the proposed recognition method of the student's identification card.

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Comparisons of Recognition Rates for the Off-line Handwritten Hangul using Learning Codes based on Neural Network (신경망 학습 코드에 따른 오프라인 필기체 한글 인식률 비교)

  • Kim, Mi-Young;Cho, Yong-Beom
    • Journal of IKEEE
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    • v.2 no.1 s.2
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    • pp.150-159
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    • 1998
  • This paper described the recognition of the Off-line handwritten Hangul based on neural network using a feature extraction method. Features of Hangul can be extracted by a $5{\times}5$ window method which is the modified $3{\times}3$ mask method. These features are coded to binary patterns in order to use neural network's inputs efficiently. Hangul character is recognized by the consonant, the vertical vowel, and the horizontal vowel, separately. In order to verify the recognition rate, three different coding methods were used for neural networks. Three methods were the fixed-code method, the learned-code I method, and the learned-code II method. The result was shown that the learned-code II method was the best among three methods. The result of the learned-code II method was shown 100% recognition rate for the vertical vowel, 100% for the horizontal vowel, and 98.33% for the learned consonants and 93.75% for the new consonants.

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A study on implementation of optical high-speed multiplier using multiplier bit-pair recoding derived from Booth algorithm (Booth 알고리즘의 승수 비트-쌍 재코딩을 이용한 광곱셈기의 구현에 관한 연구)

  • 조웅호;김종윤;노덕수;김수중
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.35D no.10
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    • pp.107-115
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    • 1998
  • A multiplier bit-pair recoding technique derived from Booth algorithm is used as an effective method that can carry out a fast binary multiplication regardless of a sign of both multiplicand and multiplier. In this paper, we propose an implementation of an optical high-speed multiplier which consists of a symbolic substitution adder and an optical multiplication algorithm, which transforms and enhances the multiplier bit-pair recoding algorithm to be fit for optical characteristics. Specially, a symbolic substitution addition rules are coded with a dual-rail logic, and so the complement of the logic of the symbolic substitution adder is easily obtained with a shift operation because it is always present. We also construct the symbolic substitution system which makes superposition image by superimposing two shifted images in a serial connection and recognizes a reference image by feeding this superimposed image to a mask. Thus, the optical multiplier, which is compared with a typical system, is implemented to the smaller system by reducing the number of optical passive elements and the size of this system.

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The Effects of Doping Hafnium on Device Characteristics of $SnO_2$ Thin-film Transistors

  • Sin, Sae-Yeong;Mun, Yeon-Geon;Kim, Ung-Seon;Park, Jong-Wan
    • Proceedings of the Korean Vacuum Society Conference
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    • 2011.02a
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    • pp.199-199
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    • 2011
  • Recently, Thin film transistors (TFTs) with amorphous oxide semiconductors (AOSs) can offer an important aspect for next generation displays with high mobility. Several oxide semiconductor such as ZnO, $SnO_2$ and InGaZnO have been extensively researched. Especially, as a well-known binary metal oxide, tin oxide ($SnO_2$), usually acts as n-type semiconductor with a wide band gap of 3.6eV. Over the past several decades intensive research activities have been conducted on $SnO_2$ in the bulk, thin film and nanostructure forms due to its interesting electrical properties making it a promising material for applications in solar cells, flat panel displays, and light emitting devices. But, its application to the active channel of TFTs have been limited due to the difficulties in controlling the electron density and n-type of operation with depletion mode. In this study, we fabricated staggered bottom-gate structure $SnO_2$-TFTs and patterned channel layer used a shadow mask. Then we compare to the performance intrinsic $SnO_2$-TFTs and doping hafnium $SnO_2$-TFTs. As a result, we suggest that can be control the defect formation of $SnO_2$-TFTs by doping hafnium. The hafnium element into the $SnO_2$ thin-films maybe acts to control the carrier concentration by suppressing carrier generation via oxygen vacancy formation. Furthermore, it can be also control the mobility. And bias stability of $SnO_2$-TFTs is improvement using doping hafnium. Enhancement of device stability was attributed to the reduced defect in channel layer or interface. In order to verify this effect, we employed to measure activation energy that can be explained by the thermal activation process of the subthreshold drain current.

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