• Title/Summary/Keyword: vector computer

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Accuracy Improvement of Frame Interpolation Algorithm using Wedge-shaped Block Partitioning (비정방형 블록을 이용한 보간 프레임의 정확도 향상 기법)

  • Jeong, Jae Heon;Jung, Ho Sun;Sunwoo, Myung Hoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.5
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    • pp.85-91
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    • 2015
  • This paper presents a novel frame rate up-conversion (FRUC) algorithm. Existing algorithms, in general, employ rectangular blocks for motion estimation and arbitrary shape of an actual object region cannot be precisely represented. On the other hand, the proposed wedge-shaped block partitioning algorithm partitions a rectangular block into two wedge-shaped blocks using the texture information, which makes better approximation for an actual object region. The wedge-shaped block partitioning algorithm as well as the adaptive motion vector prediction algorithm is used to reliably estimate the actual motion. Experimental results show that the proposed FRUC algorithm is superior to existing algorithms up to 1.988dB in PSNR and 0.0167 in SSIM comparisons.

A Study on the Multi-View Based Computer Aided Diagnosis in Digital Mammography (디지털 유방영상에서 멀티영상 기반의 컴퓨터 보조 진단에 관한 연구)

  • Choi, Hyoung-Sik;Cho, Yong-Ho;Cho, Baek-Hwan;Moon, Woo-Kyoung;Im, Jung-Gi;Kim, In-Young;Kim, Sun-I.
    • Journal of Biomedical Engineering Research
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    • v.28 no.1
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    • pp.162-168
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    • 2007
  • For the past decade, the full-field digital mammography has been widely used for early diagnosis of breast cancer, and computer aided diagnosis has been developed to assist physicians as a second opinion. In this study, we try to predict the breast cancer using both mediolateral oblique(MLO) view and craniocaudal(CC) view together. A skilled radiologist selected 35 pairs of ROIs from both MLO view and CC view of digital mammogram. We extracted textural features using Spatial Grey Level Dependence matrix from each mammogram and evaluated the generalization performance of the classifier using Support Vector Machine. We compared the multi-view based classifier to single-view based classifier that is built from each mammogram view. The results represent that the multi-view based computer aided diagnosis in digital mammogram could improve the diagnostic performance and have good possibility for clinical use to assist physicians as a second opinion.

A clustering algorithm based on dynamic properties in Mobile Ad-hoc network (에드 혹 네트워크에서 노드의 동적 속성 기반 클러스터링 알고리즘 연구)

  • Oh, Young-Jun;Woo, Byeong-Hun;Lee, Kang-Whan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.3
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    • pp.715-723
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    • 2015
  • In this paper, we propose a context-awareness routing algorithm DDV (Dynamic Direction Vector)-hop algorithm in Mobile Ad Hoc Networks. The existing algorithm in MANET, it has a vulnerability that the dynamic network topology and the absence of network expandability of mobility of nodes. The proposed algorithm performs cluster formation using a range of direction and threshold of velocity for the base-station, we calculate the exchange of the cluster head node probability using the direction and velocity for maintaining cluster formation. The DDV algorithm forms a cluster based on the cluster head node. As a result of simulation, our scheme could maintain the proper number of cluster and cluster members regardless of topology changes.

Particle Motion Interpolation Method for Mitigating the Occurrence of Unnatural Wave Breaking in Fluid Simulation (유체 시뮬레이션에서 부자연스러운 쇄파의 발생을 완화하기 위한 파티클 움직임 보간 방법)

  • Sung, Su-Kyung;Lee, Eun-Seok;Shin, Byeong-Seok
    • Journal of Korea Game Society
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    • v.14 no.3
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    • pp.55-62
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    • 2014
  • In particle-based fluid simulation, applying sudden power to particle raise unnatural flow when wave is breaking. To solve this problem, we have used an linear interpolation technique that interpolate between fluid particle by subdividing the time interval in the previous work. Acceleration vector of the particle with increased pressure in boundary could change smoothly. However, particle looks like flow with viscosity because the number of the minimum samples to interpolate increases. We propose an weighted-interpolation technique to represent the realistic movement of fluid. it is accumulating that has added and assigned different weights to the previous acceleration vector and current one repeatedly. weighted-interpolation technique using less minium samples to flow than linear interpolation, so it can solve the problem which particle looks like flow with viscosity.

Study on Fast HEVC Encoding with Hierarchical Motion Vector Clustering (움직임 벡터의 계층적 군집화를 통한 HEVC 고속 부호화 연구)

  • Lim, Jeongyun;Ahn, Yong-Jo;Sim, Donggyu
    • Journal of Broadcast Engineering
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    • v.21 no.4
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    • pp.578-591
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    • 2016
  • In this paper, the fast encoding algorithm in High Efficiency Video Coding (HEVC) encoder was studied. For the encoding efficiency, the current HEVC reference software is divided the input image into Coding Tree Unit (CTU). then, it should be re-divided into CU up to maximum depth in form of quad-tree for RDO (Rate-Distortion Optimization) in encoding precess. But, it is one of the reason why complexity is high in the encoding precess. In this paper, to reduce the high complexity in the encoding process, it proposed the method by determining the maximum depth of the CU using a hierarchical clustering at the pre-processing. The hierarchical clustering results represented an average combination of motion vectors (MV) on neighboring blocks. Experimental results showed that the proposed method could achieve an average of 16% time saving with minimal BD-rate loss at 1080p video resolution. When combined the previous fast algorithm, the proposed method could achieve an average 45.13% time saving with 1.84% BD-rate loss.

Speed-limit Sign Recognition Using Convolutional Neural Network Based on Random Forest (랜덤 포레스트 분류기 기반의 컨벌루션 뉴럴 네트워크를 이용한 속도제한 표지판 인식)

  • Lee, EunJu;Nam, Jae-Yeal;Ko, ByoungChul
    • Journal of Broadcast Engineering
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    • v.20 no.6
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    • pp.938-949
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    • 2015
  • In this paper, we propose a robust speed-limit sign recognition system which is durable to any sign changes caused by exterior damage or color contrast due to light direction. For recognition of speed-limit sign, we apply CNN which is showing an outstanding performance in pattern recognition field. However, original CNN uses multiple hidden layers to extract features and uses fully-connected method with MLP(Multi-layer perceptron) on the result. Therefore, the major demerit of conventional CNN is to require a long time for training and testing. In this paper, we apply randomly-connected classifier instead of fully-connected classifier by combining random forest with output of 2 layers of CNN. We prove that the recognition results of CNN with random forest show best performance than recognition results of CNN with SVM (Support Vector Machine) or MLP classifier when we use eight speed-limit signs of GTSRB (German Traffic Sign Recognition Benchmark).

A Tensor Space Model based Semantic Search Technique (텐서공간모델 기반 시멘틱 검색 기법)

  • Hong, Kee-Joo;Kim, Han-Joon;Chang, Jae-Young;Chun, Jong-Hoon
    • The Journal of Society for e-Business Studies
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    • v.21 no.4
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    • pp.1-14
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    • 2016
  • Semantic search is known as a series of activities and techniques to improve the search accuracy by clearly understanding users' search intent without big cognitive efforts. Usually, semantic search engines requires ontology and semantic metadata to analyze user queries. However, building a particular ontology and semantic metadata intended for large amounts of data is a very time-consuming and costly task. This is why commercialization practices of semantic search are insufficient. In order to resolve this problem, we propose a novel semantic search method which takes advantage of our previous semantic tensor space model. Since each term is represented as the 2nd-order 'document-by-concept' tensor (i.e., matrix), and each concept as the 2nd-order 'document-by-term' tensor in the model, our proposed semantic search method does not require to build ontology. Nevertheless, through extensive experiments using the OHSUMED document collection and SCOPUS journal abstract data, we show that our proposed method outperforms the vector space model-based search method.

The Public Key Polynomial Cryptosystem for Data Security in Communication Networks (통신 네트워크의 정보보호를 위한 공개키 다항식 암호시스템)

  • Yang, Tae-Kyu
    • The Journal of Information Technology
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    • v.6 no.4
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    • pp.59-68
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    • 2003
  • In this paper, a public key kanpsack cryptosystem algorithm is based on the security to a difficulty of polynomial factorization in computer communication is proposed. For the proposed public key kanpsack cryptosystem, a polynomial vector B(x,y,z) is formed by transform of superincreasing vector A, a polynomial f(x,y,z) is selected. Next then, the two polynomials B(x,y,z) and f(x,y,z) is decided on the public key. Therefore a public key knapsack cryptosystem is based on the security to a difficulty of factorization of a polynomial f(x,y,z)=0 with three variables. In this paper, a public key encryption algorithm for data security of computer network is proposed. This is based on the security to a difficulty of factorization. For the proposed public key encryption, the public key generation algorithm selects two polynomials f(x,y,z) and g(x,y,z). The propriety of the proposed public key cryptosystem algorithm is verified with the computer simulation.

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Common-mode Voltage Reduction of Three Level Four Leg PWM Converter (3레벨 4레그 PWM 컨버터의 커먼 모드 전압 저감)

  • Chee, Seung-Jun;Ko, Sanggi;Kim, Hyeon-Sik;Sul, Seung-Ki
    • The Transactions of the Korean Institute of Power Electronics
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    • v.19 no.6
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    • pp.488-493
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    • 2014
  • This paper presents a carrier-based pulse-width modulation(PWM) method for reducing the common-mode voltage of a three-level four-leg converter. The idea of the proposed PWM method is intuitive and easy to be implemented in digital signal processor-based converter control systems. On the basis of the analysis of space-vector PWM(SVPWM) and sinusoidal PWM(SPWM) switching patterns, the fourth leg pole voltage of the three-phase converter called "f leg pole voltage" is manipulated to reduce the common-mode voltage. To synthesize f leg pole voltage for the suppression of the common-mode voltage, positive and negative pole voltage references of f leg are calculated. An offset voltage is also deduced to prevent the distortion of a, b, and c phase voltages. The feasibility of the proposed PWM method is verified by simulation and experimental results. The common-mode voltage of the proposed PWM method in peak-to-peak value is 33% in comparison with that of the conventional SVPWM method. The transition number of the common-mode voltage is also reduced to 25%.

Hybrid Coding for Multi-spectral Satellite Image Compression (다중스펙트럼 위성영상 압축을 위한 복합부호화 기법)

  • Jung, Kyeong-Hoon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.1
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    • pp.1-11
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    • 2000
  • The hybrid coding algorithm for multi-spectral image obtained from satellite is discussed. As the spatial and spectral resolution of satellite image are rapidly increasing, there are enormous amounts of data to be processed for computer processing and data transmission. Therefore an efficient coding algorithm is essential for multi-spectral image processing. In this paper, VQ(vector quantization), quadtree decomposition, and DCT(discrete cosine transform) are combined to compress the multi-spectral image. VQ is employed for predictive coding by using the fact that each band of multi-spectral image has the same spatial feature, and DCT is for the compression of residual image. Moreover, the image is decomposed into quadtree structure in order to allocate the data bit according to the information content within the image block to improve the coding efficiency. Computer simulation on Landsat TM image shows the validity of the proposed coding algorithm.

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