• 제목/요약/키워드: Local Matching

검색결과 414건 처리시간 0.023초

A Technique for On-line Automatic Signature Verification based on a Structural Representation (필기의 구조적 표현에 의한 온라인 자동 서명 검증 기법)

  • Kim, Seong-Hoon;Jang, Mun-Ik;Kim, Jai-Hie
    • The Transactions of the Korea Information Processing Society
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    • 제5권11호
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    • pp.2884-2896
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    • 1998
  • For on-line signature verification, the local shape of a signature is an important information. The current approaches, in which signatures are represented into a function of time or a feature vector without regarding of local shape, have not used the various features of local shapes, for example, local variation of a signer, local complexity of signature or local difficulty of forger, and etc. In this paper, we propose a new technique for on-line signature verification based on a structural signature representation so as to analyze local shape and to make a selection of important local parts in matching process. That is. based on a structural representation of signature, a technique of important of local weighting and personalized decision threshold is newly introduced and its experimental results under different conditions are compared.

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A Comparison of PCA, LDA, and Matching Methods for Face Recognition (얼굴인식을 위한 PCA, LDA 및 정합기법의 비교)

  • 박세제;박영태
    • Journal of KIISE:Software and Applications
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    • 제30권3_4호
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    • pp.372-378
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    • 2003
  • Limitations on the linear discriminant analysis (LDA) for face rerognition, such as the loss of generalization and the computational infeasibility, are addressed and illustrated for a small number of samples. The principal component analysis (PCA) followed by the LDA mapping may be an alternative that ran overcome these limitations. We also show that any schemes based on either mappings or template matching are vulnerable to image variations due to rotation, translation, facial expressions, or local illumination conditions. This entails the importance of a proper preprocessing that can compensate for such variations. A simple template matching, when combined with the geometrically correlated feature-based detection as a preprocessing, is shown to outperform mapping techniques in terms of both the accuracy and the robustness to image variations.

MOTION VECTOR DETECTION ALGORITHM USING THE STEEPEST DESCENT METHOD EFFECTIVE FOR AVOIDING LOCAL SOLUTIONS

  • Konno, Yoshinori;Kasezawa, Tadashi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.460-465
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    • 2009
  • This paper presents a new algorithm that includes a mechanism to avoid local solutions in a motion vector detection method that uses the steepest descent method. Two different implementations of the algorithm are demonstrated using two major search methods for tree structures, depth first search and breadth first search. Furthermore, it is shown that by avoiding local solutions, both of these implementations are able to obtain smaller prediction errors compared to conventional motion vector detection methods using the steepest descent method, and are able to perform motion vector detection within an arbitrary upper limit on the number of computations. The effects that differences in the search order have on the effectiveness of avoiding local solutions are also presented.

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Fingerprint Image Quality Assessment for On-line Fingerprint Recognition (온라인 지문 인식 시스템을 위한 지문 품질 측정)

  • Lee, Sang-Hoon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • 제47권2호
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    • pp.77-85
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    • 2010
  • Fingerprint image quality checking is one of the most important issues in on-line fingerprint recognition because the recognition performance is largely affected by the quality of fingerprint images. In the past, many related fingerprint quality checking methods have typically considered the local quality of fingerprint. However, It is necessary to estimate the global quality of fingerprint to judge whether the fingerprint can be used or not in on-line recognition systems. Therefore, in this paper, we propose both local and global-based methods to calculate the fingerprint quality. Local fingerprint quality checking algorithm considers both the condition of the input fingerprints and orientation estimation errors. The 2D gradients of the fingerprint images were first separated into two sets of 1D gradients. Then,the shapes of the PDFs(Probability Density Functions) of these gradients were measured in order to determine fingerprint quality. And global fingerprint quality checking method uses neural network to estimate the global fingerprint quality based on local quality values. We also analyze the matching performance using FVC2002 database. Experimental results showed that proposed quality check method has better matching performance than NFIQ(NIST Fingerprint Image Quality) method.

A Method for Finger Vein Recognition using a New Matching Algorithm (새로운 정합 알고리즘을 이용한 손가락 정맥 인식 방법)

  • Kim, Hee-Sung;Cho, Jun-Hee
    • Journal of KIISE:Software and Applications
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    • 제37권11호
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    • pp.859-865
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    • 2010
  • In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.

An Improvement Study on the Hydrological Quantitative Precipitation Forecast (HQPF) for Rainfall Impact Forecasting (호우 영향예보를 위한 수문학적 정량강우예측(HQPF) 개선 연구)

  • Yoon Hu Shin;Sung Min Kim;Yong Keun Jee;Young-Mi Lee;Byung-Sik Kim
    • Journal of Korean Society of Disaster and Security
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    • 제15권4호
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    • pp.87-98
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    • 2022
  • In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

Local Stereo Matching Method based on Improved Matching Cost and Disparity Map Adjustment (개선된 정합 비용 및 시차 지도 재생성 기반 지역적 스테레오 정합 기법)

  • Kang, Hyun Ryun;Yun, In Yong;Kim, Joong Kyu
    • Journal of the Institute of Electronics and Information Engineers
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    • 제54권5호
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    • pp.65-73
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    • 2017
  • In this paper, we propose a stereo matching method to improve the image quality at the hole and the disparity discontinuity regions. The stereo matching method extracts disparity map finding corresponding points between stereo image pair. However conventional stereo matching methods have a problem about the tradeoff between accuracy and precision with respect to the length of the baseline of the stereo image pair. In addition, there are hole and disparity discontinuity regions which are caused by textureless regions and occlusion regions of the stereo image pair. The proposed method extracts initial disparity map improved at disparity discontinuity and miss-matched regions using modified AD-Census-Gradient method and adaptive weighted cost aggregation. And then we conduct the disparity map refinement to improve at miss-matched regions, while also improving the accuracy of the image. Experimental results demonstrate that the proposed method produces high-quality disparity maps by successfully improving miss-matching regions and accuracy while maintaining matching performance compared to existing methods which produce disparity maps with high matching performance. And the matching performance is increased about 3.22(%) compared to latest stereo matching methods in case of test images which have high error ratio.

Visual Semantic Based 3D Video Retrieval System Using HDFS

  • Ranjith Kumar, C.;Suguna, S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권8호
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    • pp.3806-3825
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    • 2016
  • This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose we intent to hitch on BOVW and Mapreduce in 3D framework. Here, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook. Further, matching is performed using soft weighting scheme with L2 distance function. As a final step, retrieved results are ranked according to the Index value and produce results .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we fiture the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

LED Backlight Driving Circuits and Dimming Method

  • Kwon, Oh-Kyong;Jung, Young-Ho;Lee, Yong-Hak;Cho, Hyun-Suk;Nam, Ki-Soo;In, Hai-Jung
    • Journal of Information Display
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    • 제11권4호
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    • pp.173-181
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    • 2010
  • In this paper, light-emitting-diode (LED) backlight driving circuits and dimming method for medium-sized and large liquid crystal displays (LCDs) are proposed. The double loop control method, the intelligent-phase-shifted PWM dimming method, the fast-switching current regulator, and the current matching techniques are proposed to improve not only the current regulation characteristics and the power efficiency but also the current matching characteristics and the transient response of the LED current. The brightness of the backlight using the proposed local dimming method was determined from the histogram of the local block to reduce the power consumption of the backlight without image distortion. The measured maximum power efficiency of the LED backlight driving circuit for medium-sized LCDs was 90%, and the simulation results showed an 88% maximum power efficiency of the LED backlight driving circuit for large LCDs. The maximum backlight power-saving ratio of the proposed dimming method was 41.7% in the simulation with a high-contrast image. The experiment and simulation results showed that the performance of LEDs as LCD backlight units (BLUs) improved with the proposed circuits and method.

An Adaptive Search Range Decision Algorithm for Fast Motion Estimation using Local Statistics of Neighboring Blocks (고속 움직임 추정을 위한 인접 블록 국부 통계 기반의 적응 탐색 영역 결정 방식)

  • 김지희;김철우;김후종;홍민철
    • Journal of Broadcast Engineering
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    • 제7권4호
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    • pp.310-316
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    • 2002
  • In this paper, we propose an adaptive search range decision algorithm for fast motion estimation of video coding. Block matching algorithm for motion vector estimation that improves coding efficiency by reduction of temporal redundancy has trade-off problem between the motion vector accuracy and the complexity. The proposed algorithm playing as a pre-processing of fast motion estimation adaptively determines the motion search range by the local statistics of neighboring motion vectors. resulting in dramatic reduction of the computational cost without the loss of coding efficiency. Experimental results show the capability of the proposed algorithm.