• Title/Summary/Keyword: color matching

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Implementation of Intelligent Expert System for Color Matching (칼라 매칭을 위한 지능형 전문 시스템의 구현)

  • Jang, Kyung-Won;Lee, Jong-Seok;Ahn, Tae-Chon;Yoon, Yang-Woong
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2768-2770
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    • 2001
  • 본 논문은 지능형 알고리즘과 이미지 프로세싱 방법을 결합한 새로운 방법으로 칼라 매칭 시스템에 구현한다. 칼라 매칭 시스템은 이미지 프로세싱을 이용하여 칼라의 RGB 데이터를 분석한 후 얻어진 색상정보를 가지고 사용자가 원하는 칼라는 구현하는 시스템이다. 칼라 매칭 시스템의 모델링에 이용되는 지능형 모델은 퍼지 추론과 적응 퍼지 추론 시스템(Adaptive Neuro-Fuzzy Inference System: ANFIS)이며, 최소 자승법을 기반으로 한 회귀 다항식과 비교하여 제안된 지능형 모델에 대한 성능과 실용성을 검증한 후 델파이를 이용하여 구현하였다.

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A Stereo Pair Matching Method Using Random Color Pattern Projection (랜덤컬러패턴을 이용한 스테레오 정합법)

  • Kim, Gi-Seon;Choi, Ran;Park, Jun-Young;Cho, Chang-Suk
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.499-502
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    • 2012
  • 문양이나 패턴이 없는 민 무늬의 물체에는 동일점 정합에 의해 3 차원 계측을 하는 스테레오 정합방식을 적용할 수 없다. 본 논문에서는 난수 발생 함수로 제작한 랜덤 칼라 패턴을 대상물체에 투영하여, 대상 물체 표면에 특징적인 문양을 인위적으로 생성시키는 것에 의해 민 무늬의 물체를 스테레오 정합법으로 측정하는 방식을 제안한다. 투사된 패턴으로 자체 문양을 지니게 된 물체를 스테레오 카메라로 촬영하였고, 동일점 정합은 전역 스테레오 정합 방식의 일종인 TRW 방식에 의한 컬러 매칭 방식을 사용하였다. 제안된 방식은 원형의 흰색 석고상 3 차원 계측에 적용되었고, 안정적이고 정확한 스테레오 정합 계측 결과를 보였다.

Implementation of Object Feature Extraction within Image for Object Tracking (객체 추적을 위한 영상 내의 객체 특징점 추출 알고리즘 구현)

  • Lee, Yong-Hwan;Kim, Youngseop
    • Journal of the Semiconductor & Display Technology
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    • v.17 no.3
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    • pp.113-116
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    • 2018
  • This paper proposes a mobile image search system which uses a sensor information of smart phone, and enables running in a variety of environments, which is implemented on Android platform. The implemented system deals with a new image descriptor using combination of the visual feature (CEDD) with EXIF attributes in the target of JPEG image, and image matching scheme, which is optimized to the mobile platform. Experimental result shows that the proposed method exhibited a significant improved searching results of around 80% in precision in the large image database. Considering the performance such as processing time and precision, we think that the proposed method can be used in other application field.

Hierarchical Graph Based Segmentation and Consensus based Human Tracking Technique

  • Ramachandra, Sunitha Madasi;Jayanna, Haradagere Siddaramaiah;Ramegowda, Ramegowda
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.67-90
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    • 2019
  • Accurate detection, tracking and analysis of human movement using robots and other visual surveillance systems is still a challenge. Efforts are on to make the system robust against constraints such as variation in shape, size, pose and occlusion. Traditional methods of detection used the sliding window approach which involved scanning of various sizes of windows across an image. This paper concentrates on employing a state-of-the-art, hierarchical graph based method for segmentation. It has two stages: part level segmentation for color-consistent segments and object level segmentation for category-consistent regions. The tracking phase is achieved by employing SIFT keypoint descriptor based technique in a combined matching and tracking scheme with validation phase. Localization of human region in each frame is performed by keypoints by casting votes for the center of the human detected region. As it is difficult to avoid incorrect keypoints, a consensus-based framework is used to detect voting behavior. The designed methodology is tested on the video sequences having 3 to 4 persons.

A Video Traffic Flow Detection System Based on Machine Vision

  • Wang, Xin-Xin;Zhao, Xiao-Ming;Shen, Yu
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1218-1230
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    • 2019
  • This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

Improved Binarization and Removal of Noises for Effective Extraction of Characters in Color Images (컬러 영상에서 효율적 문자 추출을 위한 개선된 2치화 및 잡음 저거)

  • 이은주;정장호
    • Journal of Information Technology Application
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    • v.3 no.2
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    • pp.133-147
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    • 2001
  • This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.

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INFLUENCE OF THE SHADE GUIDE DESIGN ON COLOR HATCHING (Shade guide의 형태가 색상 결정에 미치는 영향)

  • Park, Geol;Kim, Dong-Jun;Lee, Shee-Eun;Hwang, Yun-Chan;Oh, Won-Mann;Hwang, In-Nam
    • Restorative Dentistry and Endodontics
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    • v.30 no.3
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    • pp.170-177
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    • 2005
  • This study was conducted in order to assess whether the form of the shade guide affects in deciding the color of the teeth using the shade guide Eight shade light cured composite resins (Esthet-X, Dentsply, Milford, USA) were used in this study. Shade guides including the model of maxillary central incisors, teeth-form shade guide, doughnut form shade guide, and shade guide with perforated gray shield were prepared with eight shade composite resins and provided the codes randomly After arranging the models of teeth, 19 dentists working at the clinic of the Dentistry of Chonnam University Hospital and 65 students of college of dentistry, Chonnnam University selected the shade guides corresponding to the color of each tooth on the gray board under the D$_{65}$ standard illuminant. Bl shade showed highest accuracy of about 95% among all shade guides of 3 forms applied to the test and regardless of observer, tooth form shade guide showed the highest accuracy (p < 0.05) , and the doughnut form showed the lowest accuracy (p < 0.05). At the time of deciding on the color of the teeth using the shade guides as a result of above, the forms of the shade guides can affect the accuracy, and it suggests that the development of the diversified forms of shade guides, which may obtain more accurate results, is required.

Vision-based Localization for AUVs using Weighted Template Matching in a Structured Environment (구조화된 환경에서의 가중치 템플릿 매칭을 이용한 자율 수중 로봇의 비전 기반 위치 인식)

  • Kim, Donghoon;Lee, Donghwa;Myung, Hyun;Choi, Hyun-Taek
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.8
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    • pp.667-675
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    • 2013
  • This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

Segmentation of Target Objects Based on Feature Clustering in Stereoscopic Images (입체영상에서 특징의 군집화를 통한 대상객체 분할)

  • Jang, Seok-Woo;Choi, Hyun-Jun;Huh, Moon-Haeng
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.10
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    • pp.4807-4813
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    • 2012
  • Since the existing methods of segmenting target objects from various images mainly use 2-dimensional features, they have several constraints due to the shortage of 3-dimensional information. In this paper, we therefore propose a new method of accurately segmenting target objects from three dimensional stereoscopic images using 2D and 3D feature clustering. The suggested method first estimates depth features from stereo images by using a stereo matching technique, which represent the distance between a camera and an object from left and right images. It then eliminates background areas and detects foreground areas, namely, target objects by effectively clustering depth and color features. To verify the performance of the proposed method, we have applied our approach to various stereoscopic images and found that it can accurately detect target objects compared to other existing 2-dimensional methods.

The Model based Tracking using the Object Tracking method in the Sequence Scene (장면 전환에서의 물체 추적을 통한 모델기반추적 방법 연구)

  • Kim, Se-Hoon;Hwang, Jung-Won;Kim, Ki-Sang;Choi, Hyung-Il
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.775-778
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    • 2008
  • Augmented Reality is a growing area in virtual reality research, The world environment around us provides a wealth of information that is difficult to duplicate in a computer. This evidenced by the worlds used in virtual environments. An augmented reality system generates a composite view for the user. It is a combination of the real scene viewed by the user and a virtual scene generated by the computer that augments the scene with addition information. The registration method represent to the user enhances that person's performance in and perception of the world. It decide the direction and location between real world and 3D graphic objects. The registration method devide two method, Model based tracking and Move-Matching. This paper researched at to generate a commerce correlation using a tracking object method, using at a color distribution and information, in the sequence scene.

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