• 제목/요약/키워드: Color Image Processing

검색결과 1,047건 처리시간 0.031초

디지털 이미지 프로세싱 기반 토색 분석을 위한 CIELAB 색 표시계 활용 연구 (Using the CIELAB Color System for Soil Color Identification Based on Digital Image Processing)

  • 백성하;박가현;전준서;곽태영
    • 한국지반공학회논문집
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    • 제38권5호
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    • pp.61-71
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    • 2022
  • 토색은 흙을 분류하고 물리적, 화학적, 생물학적 특성을 예측하기 위한 기초 지표로 널리 활용된다. 일반적으로 토색은 육안으로 관찰해 결정하지만 관찰자의 예민도 혹은 주관이 개입될 가능성이 높으며 많은 시간이 소요된다. 디지털 이미지 프로세싱은 디지털 이미지를 이용해 원하는 정보를 획득하는 일련의 과정으로, 이를 통해 빠르고 정확한(수치적인 혹은 통계적인) 토색 분석이 가능할 것으로 기대된다. 본 연구는 현장의 불규칙한 광조건을 고려할 수 있는 디지털 이미지 프로세싱 기반 토색 분석 기술 개발을 위한 기초단계로서 수행되었다. 자연광의 특성(조도 및 색온도)을 모사할 수 있는 디지털 이미지 촬영 스튜디오를 구축하고, 두 가지 흙 시료(주문진 표준사 및 안성 풍화토)를 대상으로 광조건을 12회 씩 바꿔가며 디지털 이미지를 촬영했다. 디지털 이미지 프로세싱을 통해 촬영된 시료의 토색을 두 가지 색 표시계(RGB, CIELAB)에 대해 추출한 결과, CIELAB 색 표시계를 활용해 현장의 불규칙한 광조건을 고려할 수 있음을 확인했다.

Color Image Coding Based on Shape-Adaptive All Phase Biorthogonal Transform

  • Wang, Xiaoyan;Wang, Chengyou;Zhou, Xiao;Yang, Zhiqiang
    • Journal of Information Processing Systems
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    • 제13권1호
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    • pp.114-127
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    • 2017
  • This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation, shape coding, and texture coding. Region-of-interest (ROI) and background area are obtained by image segmentation. Shape coding uses chain code. The texture coding of the ROI is prior to the background area. SA-APBT and uniform quantization are adopted in texture coding. Compared with the color image coding algorithm based on shape-adaptive discrete cosine transform (SA-DCT) at the same bit rates, experimental results on test color images reveal that the objective quality and subjective effects of the reconstructed images using the proposed algorithm are better, especially at low bit rates. Moreover, the complexity of the proposed algorithm is reduced because of uniform quantization.

디지털 이미지 색채분석을 이용한 욕실공간 색채배색에 관한 연구 (A Study on the Color Harmony Scheme of the Bathroom Based On Digital Color Image Processing)

  • 정현원;이현수
    • 한국실내디자인학회논문집
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    • 제38호
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    • pp.217-224
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    • 2003
  • The purpose of this study is to analyze the recent trend color of bathroom based on analysis result of digital color image processing, to analyze the emotional color of that, and to suggest the harmony color combination for the bathroom. It leads to the two final results. That is, the main color of bathroom image is recognized as three color classifications such as YR-Y, Y-GY, PB-P, 2) from the point of emotional aspect, the trend color of the bathroom can be classified into four image categories: 'modern', 'mild', 'elegant', 'natural'. Finally, under these categories, this paper propose 12 color harmony schema which can be applied to color in, especially bathroom Interior design.

HSV 컬러 공간에서의 레티넥스와 채도 보정을 이용한 화질 개선 기법 (Image Quality Enhancement Method using Retinex in HSV Color Space and Saturation Correction)

  • 강한솔;고윤호
    • 한국멀티미디어학회논문지
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    • 제20권9호
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    • pp.1481-1490
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    • 2017
  • This paper presents an image quality enhancement algorithm for dark image acquired under poor lighting condition. Various retinex algorithms which are human perception-based image processing methods were proposed to solve this problem. Although MSR(Multi-Scale Retinex) among these algorithm works well under most lighting condition, it shows color degradation because their separate nonlinear processing of RGB color channels. To compensate for the loss of the color, MSRCR(Multi-Scale Retinex with Color Restoration) was proposed. However, it requires high computational load and has additional parameters that need to be adjusted according to input image. In order to overcome this problem, a new retinex algorithm based on MSR is proposed in this paper. The proposed method consists of V channel MSR, saturation correction, and separate contrast enhancement process. Experimental results show that the subjective and objective image quality of the proposed method better than those of the conventional methods.

안드로이드 기반의 스마트폰을 활용한 백반증 피부 영상 분할 (Color Image Segmentations of a Vitiligo Skin Image with Android Platform Smartphone)

  • 박상은;김현태;김정환;김경섭
    • 전기학회논문지
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    • 제63권1호
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    • pp.173-178
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    • 2014
  • In this study, the new color image processing algorithms with an android-based mobile device are developed to detect the abnormal color densities in a skin image and interpret them as the vitiligo lesions. Our proposed method is firstly based on transforming RGB data into HSI domain and segmenting the imag into the vitiligo-skin candidates by applying Otsu's threshold algorithm. The structure elements for morphological image processing are suggested to delete the spurious regions in vitiligo regions and the image blob labeling algorithm is applied to compare RGB color densities of the abnormal skin region with them of a region of interest. Our suggested color image processing algorithms are implemented with an android-platform smartphone and thus a mobile device can be utilized to diagnose or monitor the patient's skin conditions under the environments of pervasive healthcare services.

Adaptive White Point Extraction based on Dark Channel Prior for Automatic White Balance

  • Jo, Jieun;Im, Jaehyun;Jang, Jinbeum;Yoo, Yoonjong;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권6호
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    • pp.383-389
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    • 2016
  • This paper presents a novel automatic white balance (AWB) algorithm for consumer imaging devices. While existing AWB methods require reference white patches to correct color, the proposed method performs the AWB function using only an input image in two steps: i) white point detection, and ii) color constancy gain computation. Based on the dark channel prior assumption, a white point or region can be accurately extracted, because the intensity of a sufficiently bright achromatic region is higher than that of other regions in all color channels. In order to finally correct the color, the proposed method computes color constancy gain values based on the Y component in the XYZ color space. Experimental results show that the proposed method gives better color-corrected images than recent existing methods. Moreover, the proposed method is suitable for real-time implementation, since it does not need a frame memory for iterative optimization. As a result, it can be applied to various consumer imaging devices, including mobile phone cameras, compact digital cameras, and computational cameras with coded color.

OCC에서의 이미지 처리 기술 (Image processing technique for Optical Camera Communication)

  • Nguyen, Trang;Le, Nam-Tuan;Jang, Yeong Min
    • 한국위성정보통신학회논문지
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    • 제9권3호
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    • pp.47-52
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    • 2014
  • 본 논문은 이미지 처리 기술을 이용한 광 카메라 통신(OCC: Optical Camera Communications) 기술을 제안한다. OCC 시스템의 구조 및 동작을 제안한다. 상용 30fps 카메라의 샘플링 동작에 의해 제한되는 데이터율을 증가시키기 위해 칼라 이미지 처리기술을 이용한 멀티칼러 전송기법을 제안한다. 멀티칼라 부호화 및 이미지 처리기반의 복호화 기법을 제안한다.

필터링과 선형보간을 이용한 색연필스케치영상 생성 (COLOR PENCIL SKETCH IMAGE GENERATION BASED ON FILTERING AND LINEAR INTERPOLATION)

  • 애릭 히티마나;권오봉
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2012년도 추계학술발표대회
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    • pp.623-625
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    • 2012
  • In this paper, we present a method to automatically generate a color pencil sketch image from a photo. First the image is converted into a sketch using a gradient estimation and then the color pencil sketch is produced by linear interpolation with original image and the sketched image. The experimental results show that the final image has a visual aspect of a color pencil sketch like image.

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

  • 김태민;노상하
    • Journal of Biosystems Engineering
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    • 제35권2호
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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.

칼라 매저링/매칭용 지능형 전문가 시스템의 구현 (Implementation of Intelligent Expert System for Color Measuring/Matching)

  • 안태천;장경원;오성권
    • 제어로봇시스템학회논문지
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    • 제8권7호
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    • pp.589-598
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    • 2002
  • The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.