• Title/Summary/Keyword: edge labeling

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Identification of Korea Traditional Color Harmony (한국의 전통 색채 식별)

  • Baek, Jeong-Uk;Shin, Seong-Yoon;Rhee, Yang-Won
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.202-203
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    • 2009
  • In this paper, system divide into the edge extraction, labeling, clustering, and South Korea's traditional color combination and identifying to identify Korea's traditional colors. Edge is extracted using Canny operator. And given the label, and clustering to ensure the quality of the cluster. Finally, we identify color harmony by organizing and comparing primary color with secondary color configuration table Korea traditional color.

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Recognition of Color Harmony for Sensitivity Recognition (감성인식을 위한 색채 조화 인식)

  • Baek, Jeong-Uk;Shin, Seong-Yoon;Rhee, Yang-Won
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.173-174
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    • 2009
  • Color harmony will look good formative elements of the basic lines, shapes and colors. In this paper, we present the implementation of Johannes Itten's color balance. Yellow, red, blue, on the basis of the first color mixing between the index and second color is placed. 12 color balance made by placing a third color between the first color and second color. we recognize this 12 color balance. Edge is detected using the Canny edge operator and labeling and clustering was expressed through the colors.

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A Vehicle License Plate Recognition Using the Feature Vectors based on Mesh and Thinning (메쉬 및 세선화 기반 특징 벡터를 이용한 차량 번호판 인식)

  • Park, Seung-Hyun;Cho, Seong-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.705-711
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    • 2011
  • This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

Mobile Phone Camera Based Scene Text Detection Using Edge and Color Quantization (에지 및 컬러 양자화를 이용한 모바일 폰 카메라 기반장면 텍스트 검출)

  • Park, Jong-Cheon;Lee, Keun-Wang
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.3
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    • pp.847-852
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    • 2010
  • Text in natural images has a various and important feature of image. Therefore, to detect text and extraction of text, recognizing it is a studied as an important research area. Lately, many applications of various fields is being developed based on mobile phone camera technology. Detecting edge component form gray-scale image and detect an boundary of text regions by local standard deviation and get an connected components using Euclidean distance of RGB color space. Labeling the detected edges and connected component and get bounding boxes each regions. Candidate of text achieved with heuristic rule of text. Detected candidate text regions was merged for generation for one candidate text region, then text region detected with verifying candidate text region using ectilarity characterization of adjacency and ectilarity between candidate text regions. Experctental results, We improved text region detection rate using completentary of edge and color connected component.

Automatic Object Segmentation and Background Composition for Interactive Video Communications over Mobile Phones

  • Kim, Daehee;Oh, Jahwan;Jeon, Jieun;Lee, Junghyun
    • IEIE Transactions on Smart Processing and Computing
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    • v.1 no.3
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    • pp.125-132
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    • 2012
  • This paper proposes an automatic object segmentation and background composition method for video communication over consumer mobile phones. The object regions were extracted based on the motion and color variance of the first two frames. To combine the motion and variance information, the Euclidean distance between the motion boundary pixel and the neighboring color variance edge pixels was calculated, and the nearest edge pixel was labeled to the object boundary. The labeling results were refined using the morphology for a more accurate and natural-looking boundary. The grow-cut segmentation algorithm begins in the expanded label map, where the inner and outer boundary belongs to the foreground and background, respectively. The segmented object region and a new background image stored a priori in the mobile phone was then composed. In the background composition process, the background motion was measured using the optical-flow, and the final result was synthesized by accurately locating the object region according to the motion information. This study can be considered an extended, improved version of the existing background composition algorithm by considering motion information in a video. The proposed segmentation algorithm reduces the computational complexity significantly by choosing the minimum resolution at each segmentation step. The experimental results showed that the proposed algorithm can generate a fast, accurate and natural-looking background composition.

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Detection of Flaws in Air Deck using Non-Destructive Testing (비파괴 검사를 이용한 항공 갑판의 결함 검출)

  • Kim, Kwang-Baek;Cho, Jae-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.9
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    • pp.1865-1870
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    • 2011
  • In this paper, we propose an effective method that automatically detects flaws in air deck by using non-destructive testing. First, Gamma correlation transform, 7 ${\times}$ 7 and 13 ${\times}$ 13 Sobel mask apply to the image of air deck acquired non-destructive testing in order to detect the edge of the image. Second, the edge detection area is smoothed and corrected by mean binarization method. Finally, the region of flaws in air deck is detected by a labeling method after removing the noise by the erosion and the dilation operation. In experimental results, we showed that the proposed detection method is effective in air deck.

Adaptive Real-Time Ship Detection and Tracking Using Morphological Operations

  • Arshad, Nasim;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of information and communication convergence engineering
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    • v.12 no.3
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    • pp.168-172
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    • 2014
  • In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a $3{\times}3$ Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.

A Facial Region Detection using the Skin Color and Edge Information at YCbCr (YCbCr 색공간에서 피부색과 윤곽선 정보를 이용한 얼굴 영역 검출)

  • 권혁봉;권동진;장언동;윤영복;안재형
    • Journal of Korea Multimedia Society
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    • v.7 no.1
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    • pp.27-34
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    • 2004
  • This thesis proposes a face detection algorithm using the color and edge informations in color image. The proposed algorithm segments skin color by Cb and Cr in YCbCr coordinates. Then face candidate regions are made after morphological filtering and labeling. For the regions, the Sobel vortical operation and horizontal projection are performed in the Y luminance components. The peak value indicates the eye location. Similarly, the chin location is detected by the Sobel horizontal operation and horizontal projection. The computer simulation shows that the proposed method gains similar detection rates of previous method and prevent facial region from including neck by detection of chin.

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Identification of 5-Jung-color and 5-Kan-color In Video (비디오에서 오정색과 오간색 식별)

  • Shin, Seong-Yoon;Pyo, Seong-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.1
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    • pp.103-109
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    • 2010
  • As color was used for formative language since a human activity was beginning, all the symptoms in the world that the human eye can see is present. In this paper, we identify Korea traditional color harmony for extracted key frames from scene change detection. Traditional color is classified as 5-Jung-color and 5-Kan-color, and determine whether to harmony. Red, blue, yellow, black, and white, called 5-Jung-color and pink, blue, purple, sulfur, and green, called the 5-Kan-color was identified. First, we extract edge using Canny algorithm. And, we are labeling and clustering colors around the edge. Finally, we identify the traditional color using identification method of traditional color harmony. The proposed study in this paper has been proven through experiments.

Fish Injured Rate Measurement Using Color Image Segmentation Method Based on K-Means Clustering Algorithm and Otsu's Threshold Algorithm

  • Sheng, Dong-Bo;Kim, Sang-Bong;Nguyen, Trong-Hai;Kim, Dae-Hwan;Gao, Tian-Shui;Kim, Hak-Kyeong
    • Journal of Power System Engineering
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    • v.20 no.4
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    • pp.32-37
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    • 2016
  • This paper proposes two measurement methods for injured rate of fish surface using color image segmentation method based on K-means clustering algorithm and Otsu's threshold algorithm. To do this task, the following steps are done. Firstly, an RGB color image of the fish is obtained by the CCD color camera and then converted from RGB to HSI. Secondly, the S channel is extracted from HSI color space. Thirdly, by applying the K-means clustering algorithm to the HSI color space and applying the Otsu's threshold algorithm to the S channel of HSI color space, the binary images are obtained. Fourthly, morphological processes such as dilation and erosion, etc. are applied to the binary image. Fifthly, to count the number of pixels, the connected-component labeling is adopted and the defined injured rate is gotten by calculating the pixels on the labeled images. Finally, to compare the performances of the proposed two measurement methods based on the K-means clustering algorithm and the Otsu's threshold algorithm, the edge detection of the final binary image after morphological processing is done and matched with the gray image of the original RGB image obtained by CCD camera. The results show that the detected edge of injured part by the K-means clustering algorithm is more close to real injured edge than that by the Otsu' threshold algorithm.