• Title/Summary/Keyword: binarized image

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Dynamic Adaptive Binarization Method Using Fuzzy Trapezoidal Type and Image Stepwise Segmentation (퍼지의 사다리꼴 타입과 영상 단계적 분할을 이용한 동적 적응적 이진화 방법)

  • Lee, Ho Chang
    • Journal of Korea Multimedia Society
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    • v.25 no.5
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    • pp.670-675
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    • 2022
  • This study proposes an improved binarization method to improve image recognition rate. The research goal is to minimize the information loss that occurs during the binarization process, and to transform the object of the original image that cannot be determined through the transformation process into an image that can be judged. The proposed method uses a stepwise segmentation method of an image and divides blocks using prime numbers. Also, within one block, a trapezoidal type of fuzzy is applied. The fuzzy trapezoid is binarized by dividing the brightness histogram area into three parts according to the degree of membership. As a result of the experiment, information loss was minimized in general images. In addition, it was found that the converted binarized image expressed the object better than the original image in the special image in which the brightness region was tilted to one side.

An Edge-Based Adaptive Method for Removing High-Density Impulsive Noise from an Image While Preserving Edges

  • Lee, Dong-Ho
    • ETRI Journal
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    • v.34 no.4
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    • pp.564-571
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    • 2012
  • This paper presents an algorithm for removing high-density impulsive noise that generates some serious distortions in edge regions of an image. Although many works have been presented to reduce edge distortions, these existing methods cannot sufficiently restore distorted edges in images with large amounts of impulsive noise. To solve this problem, this paper proposes a method using connected lines extracted from a binarized image, which segments an image into uniform and edge regions. For uniform regions, the existing simple adaptive median filter is applied to remove impulsive noise, and, for edge regions, a prediction filter and a line-weighted median filter using the connected lines are proposed. Simulation results show that the proposed method provides much better performance in restoring distorted edges than existing methods provide. When noise content is more than 20 percent, existing algorithms result in severe edge distortions, while the proposed algorithm can reconstruct edge regions similar to those of the original image.

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.

Extraction of Characteristics of Concrete Surface Cracks

  • Ahn, Sang-Ho
    • Journal of information and communication convergence engineering
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    • v.5 no.2
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    • pp.126-130
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    • 2007
  • This paper proposes a method that automatically extracts characteristics of cracks such as length, thickness and direction, etc., from a concrete surface image with image processing techniques. This paper, first, uses the closing morphologic operation to adjust the effect of light extending over the whole concrete surface image. After applying the high-pass filtering operation to sharpen boundaries of cracks, we classify intensity values of the image into 8 groups and remove intensity values belong to the highest frequency group among them for the removal of background. Then, we binarize the preprocessed image. The auxiliary lines used to measure cracks of concrete surface are removed from the binarized image with position information extracted by the histogram operation. Then, cracks broken by the removal of background are extended to reconstruct an original crack with the $5{\times}5$ masking operation. We remove unnecessary information by applying three types of noise removal operations successively and extracts areas of cracks from the binarized image. At last, the opening morphologic operation is applied to compensate extracted cracks and characteristics of cracks are measured on the compensated ones. Experiments using real images of concrete surface showed that the proposed method extracts cracks well and precisely measures characteristics of cracks.

Recognition of Identifiers from Shipping Container Image by Using Fuzzy Binarization and ART2-based RBF Network

  • Kim, Kwang-Baek
    • Journal of Intelligence and Information Systems
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    • v.9 no.2
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    • pp.1-18
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    • 2003
  • The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

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Recognition of Concrete Surface Cracks Using Enhanced Max-Min Neural Networks (개선된 Max-Min 신경망을 이용한 콘크리트 균열 인식)

  • Kim, Kwang-Baek;Park, Hyun-Jung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.77-82
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    • 2007
  • In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the enhanced Max-Min neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation or morphological techniques, the Sobel masking for extracting for edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions of the cracks with the enhanced Max-Min neural network. Also, we propose an enhanced Max-Min neural network by auto-tuning of learning rate using delta-bar-delta algorithm. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

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Binarization and Stroke Reconstruction of Low Quality Character Image for Effective Character Recognition (효과적인 문자 인식을 위한 저 품질 문자 영상의 이진화 및 획 재구성 방법)

  • Kim, Do-Hyeon;Cha, Eui-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.3
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    • pp.608-618
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    • 2007
  • Image binarization is an important preprocessing to identify the object of interest by dividing pixels into the background and object. We proposes efficient binarization method and a stroke reconstruction method of the low quality character image for an effective character recognition. First, the character image is binarized by using the both advantages of local and global thresholding method and then the noise elimination around the character stroke and the hole filling on the stoke by the analysis of the binarized stroke image are performed to enhance the quality of the character stroke. Proposed binarization algorithm for character image achieved an efficiency of both processing speed and performance by the adaptive threshold selection. Moreover, We could get a high qualify binary image by a stroke reconstruction of the step-by-step denoising process.

Binarization Method of Night Illumination Image with Low Information Loss Using Fuzzy Logic (퍼지논리를 이용하여 정보손실이 적은 야간조명 영상의 이진화 방법 연구)

  • Lee, Ho Chang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.5
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    • pp.540-546
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    • 2019
  • This study suggests a binarization method that minimizes information loss for night illumination images. The object of the night illumination image is an image which is not focused due to the influence of illumination and is not identifiable. Also, the image has a brightness area in only a part of the brightness histogram. So the existing simple binarization method is hard to get good results. The proposed binarization method uses image segmentation method and image merging method. In the stepwise divided blocks, we divide into two regions using the triangular type of fuzzy logic. The value 0 of the membership degree is binarized at the present step, and the value of the membership degree 1 is binarized after the next step. Experimental results show that night illumination images with minimal loss of information can be obtained in a dark area brightness range.

A Study on an Infrared Illumination Stabilization Method in a Head Mounted Eye Tracking System for Sport Applications (착용형 시선 추적 장치의 스포츠 분야 적용을 위한 적외선 조명 변화 최소화에 관한 연구)

  • Lee, Sang-Cheol
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.3
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    • pp.265-272
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    • 2009
  • In this paper, a simple optical method that uses an infrared(IR) cut filter is proposed to minimize variation of eye image by external infrared(IR) sources in a video based head mounted eye tracking system that is used in the field of sports. For this, the IR cut filter is attached to a head mount of the eye tracking system, and the camera with an IR LED is located between the IR cut filter and eye. In this structure, external IR is blocked by the IR cut filter, and the IR intensity on the eye can be controlled by the IR LED. Therefore, the illumination condition of the camera to capture the eye can be stable without being affected by external IR illuminations. To verify the proposed idea, variation of the eye image and intensity of the IR with/without the IR cut filter is measured under various illumination conditions. The measured data show that the IR cut filter method can block external IR effectively, and complex pupil detection algorithms can be replaced by a simple binarized method.

Automatic Classification of SMD Packages using Neural Network (신경회로망을 이용한 SMD 패키지의 자동 분류)

  • Youn, SeungGeun;Lee, Youn Ae;Park, Tae Hyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.3
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    • pp.276-282
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    • 2015
  • This paper proposes a SMD (surface mounting device) classification method for the PCB assembly inspection machines. The package types of SMD components should be classified to create the job program of the inspection machine. In order to reduce the creation time of job program, we developed the automatic classification algorithm for the SMD packages. We identified the chip-type packages by color and edge distribution of the images. The input images are transformed into the HSI color model, and the binarized histroms are extracted for H and S spaces. Also the edges are extracted from the binarized image, and quantized histograms are obtained for horizontal and vertical direction. The neural network is then applied to classify the package types from the histogram inputs. The experimental results are presented to verify the usefulness of the proposed method.