• Title/Summary/Keyword: Intelligent image processing

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Implementation of Object Tracking System with Multi Camera by Using Background Generation Technique (배경 생성 기법을 이용한 다중 카메라 객체 추적 시스템 구현)

  • Jo, Hyun-Tae;Jang, Jae-Nee;Kang, Nam-Oh;Paik, Joon-Ki
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.947-948
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    • 2008
  • Recently, many efforts have been made for research and application of object tracking system. However, introduced object tracking algorithms have limitations to adopt a realtime object tracking system with multi camera. In this paper, we present a novel background generation and target object recognition algorithm for realtime object tracking system with multi camera and implemented it.

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Image Recognition by Learning Multi-Valued Logic Neural Network

  • Kim, Doo-Ywan;Chung, Hwan-Mook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.3
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    • pp.215-220
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    • 2002
  • This paper proposes a method to apply the Backpropagation(BP) algorithm of MVL(Multi-Valued Logic) Neural Network to pattern recognition. It extracts the property of an object density about an original pattern necessary for pattern processing and makes the property of the object density mapped to MVL. In addition, because it team the pattern by using multiple valued logic, it can reduce time f3r pattern and space fer memory to a minimum. There is, however, a demerit that existed MVL cannot adapt the change of circumstance. Through changing input into MVL function, not direct input of an existed Multiple pattern, and making it each variable loam by neural network after calculating each variable into liter function. Error has been reduced and convergence speed has become fast.

Image processing technology in urban transit system (도시철도 시스템에서 화상처리기술 역사 적용방안)

  • Oh Seh-Chan;Park Sung-Hyuk;Yeo Min-Woo
    • Proceedings of the KSR Conference
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    • 2005.11a
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    • pp.915-920
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    • 2005
  • Passenger safety is a primary concern of railway system but, it has been urgent issue that dozens of people are killed every year when they fall off from train platforms. Recently, advancements in IT have enabled applying vision sensors to railway environments, such as CCTV and various camera sensors. The objective of this work is to propose technical and system requirements for establishing intelligent monitoring system using camera equipments in urban transit system. We suppose the system is to determine automatically and in real-time whether anyone or anything is in monitoring area. To achieve the goal, we analyze recent image processing technologies for detection and recognition, and suggest possible direction of system development for applying urban transit system. According to the results, we expect the proposed system requirements will playa key role for establishing highly intelligent monitoring system in railway.

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Building the Domain Ontology for Content Based Image Retrieval System (개념기반 이미지 검색 시스템을 위한 도메인 온톨로지 구축)

  • Kong, Hyun-Jang;Kim, Won-Pil;Oh, Kun-Seok;Kim, Pan-Koo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.81-84
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    • 2002
  • 멀티미디어 분야가 급성장하면서 좀더 효율적으로 멀티미디어 자료의 저장, 처리, 검색을 위한 연구가 진행되고 있다. 특히, 내용기반 시각정보 검색에 있어 지능형 시스템(Intelligent System)을 접목하여 의미적 접근을 시도하는 I-CBIR(Intelligent-Content Based Image Retrieval)에 관한 연구가 진행되고 있다. 또한, 내용기반 이미지검색 시스템에 온톨로지(Ontology)의 이론을 적용하여 이미지에 의미를 부여하여 개념적 검색이 가능하도록 노력하고 있다. 이러한 연구에서 적용된 대형의 온톨로지는 이미지 검색 시스템에 적합하지 않게 너무 방대한 정보를 가지고 있으며, 또한 시대적 변화에 대응하지 못하여 I-CBIR 시스템에서 그 효율성을 제대로 발휘하지 못하고 있다. 따라서 본 논문에서는 많은 대형 온톨로지 중에서 WordNet을 선택하여, WordNet의 구축 방법에 기반한 자동차(Car)에 대한 도메인 온톨로지(Domain Ontology)를 구축해보고, 구축된 도메인 온톨로지를 적용함으로써 더 향상된 I-CBIR 시스템이 되도록 하였다.

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Fast Grid-Based Refine Segmentation on V-PCC encoder (V-PCC 부호화기의 그리드 기반 세그먼트 정제 고속화)

  • Kim, Yura;Kim, Yong-Hwan
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.265-268
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    • 2022
  • Video-based Point Cloud Compression(V-PCC) 부호화기의 세그먼트 정제(Refining segmentation) 과정은 3D 세그먼트를 2D 패치 데이터로 효율적으로 변환하기 위한 V-PCC 부호화기의 핵심 파트이지만, 많은 연산량을 필요로 하는 모듈이다. 때문에 이미 TMC2 에 Fast Grid-based refine segmentation 과정이 구현되어 있으나, 아직도 세그먼트 정제 기술의 연산량은 매우 높은 편이다. 본 논문에서는 현재 TMC2 에 구현되어 있는 Fast Gridbased Refine Segmentation 을 살펴보고, 복셀(Voxel) 타입에 따른 특성에 맞춰 두 가지 조건을 추가하는 고속화 알고리즘을 제안한다. 실험 결과 압축성능(BD-BR)은 TMC2 와 거의 차이를 보이지 않았지만, 모듈 단위 평균 10% 연산량이 절감되는 것을 확인하였다.

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Similarity-Based Patch Packing Method for Efficient Plenoptic Video Coding in TMIV

  • Kim, HyunHo;Kim, Yong-Hwan
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.250-252
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    • 2022
  • As immersive video contents have started to emerge in the commercial market, research on it is required. For this, efficient coding methods for immersive video are being studied in the MPEG-I Visual workgroup, and they released Test Model for Immersive Video (TMIV). In current TMIV, the patches are packed into atlas in order of patch size. However, this simple patch packing method can reduce the coding efficiency in terms of 2D encoder. In this paper, we propose patch packing method which pack the patches into atlases by using the similarity of each patch for improving coding efficiency of 3DoF+ video. Experimental result shows that there is a 0.3% BD-rate savings on average over the anchor of TMIV.

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On-line Inspection Algorithm of Brown Rice Using Image Processing (영상처리를 이용한 현미의 온라인 품위판정 알고리즘)

  • Kim, Tae-Min;Noh, Sang-Ha
    • Journal of Biosystems Engineering
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    • v.35 no.2
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    • pp.138-145
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    • 2010
  • An on-line algorithm that discriminates brown rice kernels on their echelon feeder using color image processing is presented for quality inspection. A rapid color image segmentation algorithm based on Bayesian clustering method was developed by means of the look-up table which was made from the significant clusters selected by experts. A robust estimation method was presented to improve the stability of color clusters. Discriminant analysis of color distributions was employed to distinguish nine types of brown rice kernels. Discrimination accuracies of the on-line discrimination algorithm were ranged from 72% to 85% for the sound, cracked, green-transparent and green-opaque, greater than 93% for colored, red, and unhulled, about 92% for white-opaque and 67% for chalky, respectively.

A Research on the Measurement of Human Factor Algorithm 3D Object (3차원 영상 객체 휴먼팩터 알고리즘 측정에 관한 연구)

  • Choi, Byungkwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.14 no.2
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    • pp.35-47
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    • 2018
  • The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

Image Segmentation Using A Fuzzy Neural Network (퍼지 신경회로망을 이용한 영상분할)

  • 김용수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.313-318
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    • 2000
  • Image segmentation is to divide an image into similar parts or objects. This paper presents a segmentation system which consists of a fuzzy neural network and a set of image processing filters. The fuzzy neural network does not need initialization of weights. Therefore it does not have the underutilization problem. This fuzzy neural network controls the size and number of clusters by the vigilance parameter instead of fixing the number of clusters at the initial stage. This fuzzy neural network does not require large amount of memory as in Fuzzy c-Means algorithm. Two satellite images were segmented using the proposed system. The segmented results show that the proposed system is better on segmenting images.

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Color Edge Detection using Variable Template Operator

  • Baek Young-Hyun;Moon Sung-Ryong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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    • pp.116-120
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    • 2006
  • This paper discusses an approach for detecting a new edge in color images. The color image is to be represented by a vector field, and the color image edges are detected as differences in the local vector statistics. This method is based on the calculation for the vector angle between two adjacent pixels. Unlike Euclidean distance in RGB space, the vector angle distinguishes the differences in chromaticity, independent of luminance or intensity. The proposed approach can easily accommodate concepts, such as variable template edge detection, as well as the latest developments in vector order statistics for color image processing. In this paper, it is used not a conventional fixed template operator but a variable template operator The variable template is implemented and experimental results for digital color images are included.