• Title/Summary/Keyword: Color Computer Vision

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Real Time Recognition of Finger-Language Using Color Information and Fuzzy Clustering Algorithm

  • Kim, Kwang-Baek;Song, Doo-Heon;Woo, Young-Woon
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.19-22
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    • 2010
  • A finger language helping hearing impaired people in communication A sign language helping hearing impaired people in communication is not popular to ordinary healthy people. In this paper, we propose a method for real-time sign language recognition from a vision system using color information and fuzzy clustering system. We use YCbCr color model and canny mask to decide the position of hands and the boundary lines. After extracting regions of two hands by applying 8-directional contour tracking algorithm and morphological information, the system uses FCM in classifying sign language signals. In experiment, the proposed method is proven to be sufficiently efficient.

Image Processing Software Development for Detection of Oyster Hinge Lines (굴의 힌지 선 감지를 위한 영상처리 소프트웨어의 개발)

  • So, J.D.;Wheaton, Fred W.
    • Journal of Biosystems Engineering
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    • v.22 no.2
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    • pp.237-246
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    • 1997
  • Shucking(removing the meat from the shell) an oyster requires that the muscle attachments to the two shell valves and the hinge be severed. Described here is the computer vision software needed to locate the oyster hinge line so it can be automatically severed, one step in development of an automated oyster shucker. Oysters are first prepared by washing and trimming off a small shell piece on the oyster hinge end to provide access to the outer hinge surface. A computer vision system employing a color video comera then gabs an image of the hinge end of the oyster shell. This image is Processed by the computer using software. The software is a combination of commercially available and custom written routines that locate the oyster hinge. The software uses four feature variables, circularity, rectangularity, aspect-ration, and Euclidian distance, to distinguish the hinge object from other dark colored objects on the hinge end of the oyster. Several techniques, including shrink-expand, thresholding, and others, were used to secure an image that could be reliably and efficiently processed to locate the oyster hinge line.

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Analysis of Chicken Feather Color Phenotypes Classified by K-Means Clustering using Reciprocal F2 Chicken Populations (K-Means Clustering으로 분류한 닭 깃털색 표현형의 분석)

  • Park, Jongho;Heo, Seonyeong;Kim, Minjun;Cho, Eunjin;Cha, Jihye;Jin, Daehyeok;Koh, Yeong Jun;Lee, Seung-Hwan;Lee, Jun Heon
    • Korean Journal of Poultry Science
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    • v.49 no.3
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    • pp.157-165
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    • 2022
  • Chickens are a species of vertebrate with varying colors. Various colors of chickens must be classified to find color-related genes. In the past, color scoring was performed based on human visual observation. Therefore, chicken colors have not been measured with precise standards. In order to solve this problem, a computer vision approach was used in this study. Image quantization based on k-means clustering for all pixels of RGB values can objectively distinguish inherited colors that are expressed in various ways. This study was also conducted to determine whether plumage color differences exist in the reciprocal cross lines between two breeds: black Yeonsan Ogye (YO) and White Leghorn (WL). Line B is a crossbred line between YO males and WL females while Line L is a reciprocal crossbred line between WL males and YO females. One male and ten females were selected for each F1 line, and full-sib mating was conducted to generate 883 F2 birds. The results indicate that the distribution of light and dark colors of k-means clustering converged to 7:3. Additionally, the color of Line B was lighter than that of Line L (P<0.01). This study suggests that the genes underlying plumage colors can be identified using quantification values from the computer vision approach described in this study.

Visual Saliency Detection Based on color Frequency Features under Bayesian framework

  • Ayoub, Naeem;Gao, Zhenguo;Chen, Danjie;Tobji, Rachida;Yao, Nianmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.676-692
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    • 2018
  • Saliency detection in neurobiology is a vehement research during the last few years, several cognitive and interactive systems are designed to simulate saliency model (an attentional mechanism, which focuses on the worthiest part in the image). In this paper, a bottom up saliency detection model is proposed by taking into account the color and luminance frequency features of RGB, CIE $L^*a^*b^*$ color space of the image. We employ low-level features of image and apply band pass filter to estimate and highlight salient region. We compute the likelihood probability by applying Bayesian framework at pixels. Experiments on two publically available datasets (MSRA and SED2) show that our saliency model performs better as compared to the ten state of the art algorithms by achieving higher precision, better recall and F-Measure.

Luminance Change Independent 3D Snail Tracking

  • Dewi, Primastuti;Choi, Yoen-Seok;Chon, Tae-Soo;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.175-178
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    • 2010
  • Slow movement of snail can be a benefit since it means less speed of tracking is required to get accurate movement track, but in the other side it is difficult to extract the object because the snail is almost as static as the background. In this paper, we present a technique to track the snail by using one of its common characteristic, dark color of its shell. The technique needs to be robust to illumination change since the experiment is usually to observe the movement of snail both at bright and dim condition. Snail position coordinate in 3D space is calculated using orthogonal stereo vision which combines the information from two images taken from cameras at the top and in front of the aquarium. Experimental results show this technique does not need prior background image extraction and robust to gradual or sudden illumination change.

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Lane Detection for Parking Violation Assessments

  • Kim, A-Ram;Rhee, Sang-Yong;Jang, Hyeon-Woong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.1
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    • pp.13-20
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    • 2016
  • In this study, we propose a method to regulate parking violations using computer vision technology. A still color image of the parked vehicle under question is obtained by a camera mounted on enforcement vehicles. The acquired image is preprocessed through a morphological algorithm and binarized. The vehicle's shadows are detected from the binarized image, and lanes are identified using the information from the yellow parking lines that are drawn on the load. Whether parking is illegal is determined by the conformity of the lanes and the vehicle's shadow.

Mood and Color Distribution of Music genres (음악 장르에 따른 분위기와 색상 분포)

  • Moon, Chang-Bae;Kim, Hyun-Soo;Kim, Byeong-Man;Yi, Jong-Yeol;Suk, Jin-Weon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.04a
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    • pp.357-360
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    • 2011
  • 스트레스는 다양한 질병의 원인이 되며 스트레스의 해소는 질병 예방에 중요한 요인이라 할 수 있을 것이다. 스트레스를 해소시키는 방법 중 한 가지는 청각이나 시각을 이용하는 방법이다. 청각과 시각을 동시에 이용할 수 있다면 그 효과를 극대화 할 수 있을 것이다. 이러한 맥락에서 본 논문에서는 음원의 분위기와 분위기 단어의 색상을 수집한 후 수집한 데이터를 이용하여 음악 장르에 따른 분위기 분포와 분위기 단어에 따른 색상을 이용하여 음악 장르에 따른 색상 분포가 다르다는 것을 확인하기 위해 Minitab을 이용하여 $x^2$-test를 실시하였다. 분석결과, P<0.001로 음악 장르에 따라 분위기 색상이 다르게 분포되며 분위기에 따라 색상 및 명도, 채도의 분포도 다르게 나타남을 확인하였다.

Development of Assistive Software for color blind to Electronic Documents (전자문서용 색각 장애 보정 소프트웨어 개발)

  • Jang, Young-Gun
    • The KIPS Transactions:PartB
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    • v.10B no.5
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    • pp.535-542
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    • 2003
  • This study is concerned with an assistive technology which reduces color blinds´s confusion when they access electronic documents including color objects in their computers. In this study, 1 restrict the assistive technology would apply to windows operating system, 256 color mode and implement to minimize color distortion which occurs in multi window environments because of color approximation process. As a basic palette, I use a 216 colors web safe palette which the Christine proposed as a standard for color blind, expand it to 256 colors to apply all computer displays using Microsoft Windows as its operating system and implement it as windows application. To test its effectiveness, I use a simulator for dichromats, as results of the test, the developed color vision deficiency correction S/W is effective to reduce the confusion. It is more effective to use the implemented S/W in both of design and client process for electronic documents.

Color Analysis with Enhanced Fuzzy Inference Method (개선된 퍼지 추론 기법을 이용한 칼라 분석)

  • Kim, Kwang-Baek
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.8
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    • pp.25-31
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    • 2009
  • Widely used color information recognition methods based on the RGB color model with static fuzzy inference rules have limitations due to the model itself-the detachment of human vision and applicability of limited environment. In this paper, we propose a method that is based on HSI model with new inference process that resembles human vision recognition process. Also, a user can add, delete, update the inference rules in this system. In our method, we design membership intervals with sine, cosine function in H channel and with functions in trigonometric style in S and I channel. The membership degree is computed via interval merging process. Then, the inference rules are applied to the result in order to infer the color information. Our method is proven to be more intuitive and efficient compared with RGB model in experiment.

A Comparison of Superpixel Characteristics based on SLIC(Simple Linear Iterative Clustering) for Color Feature Spaces (칼라특징공간별 SLIC기반 슈퍼픽셀의 특성비교)

  • Lee, Jeong Hwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.4
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    • pp.151-160
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    • 2014
  • In this paper, a comparison of superpixel characteristics based on SLIC(simple linear iterative clustering) for several color feature spaces is presented. Computer vision applications have come to rely increasingly on superpixels in recent years. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. A superpixel is consist of pixels with similar features such as luminance, color, textures etc. Thus superpixels are more efficient than pixels in case of large scale image processing. Generally superpixel characteristics are described by uniformity, boundary precision and recall, compactness. However previous methods only generate superpixels a special color space but lack researches on superpixel characteristics. Therefore we present superpixel characteristics based on SLIC as known popular. In this paper, Lab, Luv, LCH, HSV, YIQ and RGB color feature spaces are used. Uniformity, compactness, boundary precision and recall are measured for comparing characteristics of superpixel. For computer simulation, Berkeley image database(BSD300) is used and Lab color space is superior to the others by the experimental results.