• Title/Summary/Keyword: camera image

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A Comparison of System Performances Between Rectangular and Polar Exponential Grid Imaging System (POLAR EXPONENTIAL GRID와 장방형격자 영상시스템의 영상분해도 및 영상처리능력 비교)

  • Jae Kwon Eem
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.2
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    • pp.69-79
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    • 1994
  • The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

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Multispectral Wavelength Selection to Detect 'Fuji' Apple Surface Defects with Pixel-sampling Analysis

  • Park, Soo Hyun;Lee, Hoyoung;Noh, Sang Ha
    • Journal of Biosystems Engineering
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    • v.39 no.3
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    • pp.166-173
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    • 2014
  • Purpose: In this study, we focused on the image processing method to determine the external quality of Fuji apples by identifying surface defects such as scabs and bruises. Method: A CCD camera was used to capture filter images with 24 different wavelengths ranging between 530 nm and 1050 nm. Image subtraction and division operations were performed to distinguish the defect area from the normal areas including calyx, stem, and glaring on the apple surface image. All threshold values of the image were examined to reveal the defect area of pretreated filter images. Results: The developed operation methods were [image (720 nm) - image (900 nm)]/image (700 nm) for bruise detection and [image (740 nm) - image (900 nm)]/image (590 nm) for scab detection, which revealed 81% and 90% recognition ratios, respectively. Conclusions: Our results showed several optimal wavelengths and image processing methods to detect Fuji apple surface defects such as bruises and scabs.

Super-Resolution Iris Image Restoration using Single Image for Iris Recognition

  • Shin, Kwang-Yong;Kang, Byung-Jun;Park, Kang-Ryoung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.2
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    • pp.117-137
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    • 2010
  • Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

Study on Image Processing Techniques Applying Artificial Intelligence-based Gray Scale and RGB scale

  • Lee, Sang-Hyun;Kim, Hyun-Tae
    • International Journal of Advanced Culture Technology
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    • v.10 no.2
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    • pp.252-259
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    • 2022
  • Artificial intelligence is used in fusion with image processing techniques using cameras. Image processing technology is a technology that processes objects in an image received from a camera in real time, and is used in various fields such as security monitoring and medical image analysis. If such image processing reduces the accuracy of recognition, providing incorrect information to medical image analysis, security monitoring, etc. may cause serious problems. Therefore, this paper uses a mixture of YOLOv4-tiny model and image processing algorithm and uses the COCO dataset for learning. The image processing algorithm performs five image processing methods such as normalization, Gaussian distribution, Otsu algorithm, equalization, and gradient operation. For RGB images, three image processing methods are performed: equalization, Gaussian blur, and gamma correction proceed. Among the nine algorithms applied in this paper, the Equalization and Gaussian Blur model showed the highest object detection accuracy of 96%, and the gamma correction (RGB environment) model showed the highest object detection rate of 89% outdoors (daytime). The image binarization model showed the highest object detection rate at 89% outdoors (night).

Compensation Method for Occluded-region of Arbitrary-view Image Synthesized from Multi-view Video (다시점 동영상에서 임의시점영상 생성을 위한 가려진 영역 보상기법)

  • Park, Se-Hwan;Song, Hyuk;Jang, Eun-Young;Hur, Nam-Ho;Kim, Jin-Woong;Kim, Jin-Soo;Lee, Sang-Hun;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.12C
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    • pp.1029-1038
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    • 2008
  • In this paper, we propose a method for an arbitrary-view image generation in multi-view video and methods for pre- and post-processing to compensate unattended regions in the generated image. To generate an arbitrary-view image, camera geometry is used. Three dimensional coordinates of image pixels can be obtained by using depth information of multi-view video and parameter information of multi-view cameras, and by replacing three dimensional coordinates on a two dimensional image plane of other view, arbitrary-view image can be reconstructed. However, the generated arbitrary-view image contains many unattended regions. In this paper, we also proposed a method for compensating these regions considering temporal redundancy and spatial direction of an image and an error of acquired multi-view image and depth information. Test results show that we could obtain a reliably synthesized view-image with objective measurement of PSNR more than 30dB and subjective estimation of DSCQS(double stimulus continuous quality scale method) more than 3.5 point.

The Cultural Meanings of the first optical insturment, Camera obscura, in the pre-modern Age (최초의 영상기구, 카메라 옵스쿠라의 문화사적 의미)

  • LEE, Sang-Myon
    • Korean Association for Visual Culture
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    • v.16
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    • pp.131-161
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    • 2010
  • This thesis investigates the cultural meanings of the first optical instrument, Camera obscura, in the pre-modern age, while it explains the development as well as the use of the Camera obscura in Europe and Korea. For this purpose the thesis traces the significant phases of the historical developments of the Camera obscura from L. da Vinci, G. B. della Porta, D. Barbaro, A. Kircher to J. Zahn etc. The Camera obscura was not only the symbolic instrument of the modernism in the sense that human being wanted to observe the outer world by himself and to be freed from the viewpoint of the christianity, but also was the forerunner of the modern visual culture, because it first time reproduced the artificial image of the natural world. Since the second half of the 17th century the box-type reflex Camera obscura had been produced, it began to be used as aid to drawing for painters like J. Vermeer, A. Canaletto and J. Reynolds etc. throughout Europe. It tells the evidence of the close relation between art and technology in the pre-modern age. Around the end of the 18th century the Camera obscura was brought to Korea, the closed country of the Fareast, by the scholars of the so-called 'Realist school' (Silhak-pa) who went to Beijing to acquire knowledges on the Western science from the European priests. In 1780s Yak-yong JUNG, one of the representative scholars of the Realist school, experimented the Camera obscura, and then, it was used for sketches of higher aristocrats' portraits by the supreme portrait painter of that time, Myoung-ki LEE. Those were possible only under the reign of the culturally liberal and reformative King, Jung-jo (ruled 1776-1800), and after his retreatment the inquiry of the Camera obscura had been dimished. It is not a historical coincidence that the Camera obscura could be examined and used in the period of the Enlightment both in Europe and Korea.

An Image Segmentation based on Chamfer Algorithm (Chamfer 알고리듬에 기초한 영상분리 기법)

  • Kim, Hak-Kyeong;Jeong, Nam-Soo;Lee, Myung-Suk;Kim, Sang-Bong
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.670-675
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    • 2001
  • This paper is to propose image segmentation method based on chamfer algorithm. First, we get original image from CCD camera and transform it into gray image. Second, we extract maximum gray value of background and reconstruct and eliminate the background using surface fitting method and bilinear interpolation. Third, we subtract the reconstructed background from gray image to remove noises in gray image. Fourth, we transform the subtracted image into binary image using Otsu's optimal thresholding method. Fifth, we use morphological filters such as areaopen, opening, filling filter etc. to remove noises and isolated points. Sixth, we use chamfer distance or Euclidean distance to this filtered image. Finally, we use watershed algorithm and count microorganisms in image by labeling. To prove the effectiveness, we apply the proposed algorithm to one of Ammonia-oxidizing bacteria, Acinetobacter sp. It is shown that both Euclidean algorithm and chamfer algorithm show over-segmentation. But Chamfer algorithm shows less over-segmentation than Euclidean algorithm.

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Vision-based recognition of a simple non-verbal intent representation by head movements (고개운동에 의한 단순 비언어 의사표현의 비전인식)

  • Yu, Gi-Ho;No, Deok-Su;Lee, Seong-Cheol
    • Journal of the Ergonomics Society of Korea
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    • v.19 no.1
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    • pp.91-100
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    • 2000
  • In this paper the intent recognition system which recognizes the human's head movements as a simple non-verbal intent representation is presented. The system recognizes five basic intent representations. i.e., strong/weak affirmation. strong/weak negation, and ambiguity by image processing of nodding or shaking movements of head. The vision system for tracking the head movements is composed of CCD camera, image processing board and personal computer. The modified template matching method which replaces the reference image with the searched target image in the previous step is used for the robust tracking of the head movements. For the improvement of the processing speed, the searching is performed in the pyramid representation of the original image. By inspecting the variance of the head movement trajectories. we can recognizes the two basic intent representations - affirmation and negation. Also, by focusing the speed of the head movements, we can see the possibility which recognizes the strength of the intent representation.

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Measurement Technique for Sea Height of Burst Using Image Recognition

  • Park, Ju-Ho;Hong, Sung-Soo;Kang, Kyu-Chang;Joon Lyou
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.1
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    • pp.76-83
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    • 2000
  • A measurement technique of a sea height of burst is introduced for a proximate test using the image recognition of video cameras. In the burst of fuse on the ocean, the burst center of fuse, the sea surface level and the height of calibration poles are measured by the process of image obtained from cameras. Finally, the height of burst of fuse can be computed by Hough transform algorithm. The error compensation algorithms are proposed to eliminate the errors caused by camera level and environmental parameters. As a result of experiment, it has been proved that the proposed measurement system shows the recognition of the center point of the burst image with ${\pm}$0.5m error.

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Extraction of the three-dimensional surface coordinate from a stereo image (스테레오 영상을 이용한 3차원 표면좌표 추출 알고리즘)

  • 원성혁;김민기;김병우;이기식;김헌배
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.210-213
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    • 2000
  • In the closed range space, the parallel two CCD cameras are used to acquire a pair of stereo image. The acquired stereo image are computed with Wavelet Transform repeatedly and including the low frequency component, the image size of those are reduced. It is the pyramid structure. The optimum matching point is searched to the pixel. Then appling the optimum matching point to DLT, it extract the three - dimensional surface coordinate from a stereo image. The direct linear transformation(DLT) method is used to calibrate the stereo camera compute the coordinate on a three dimensional space. To find the parameters for the DLT method, 30 control points which marked on the cylinder type object are used. To improve the matching algorithm, the paper select the pyramid structure for Wavelet Transform. The acquired disparity information is used to represent the really three-dimensional surface coordinate.

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