• Title/Summary/Keyword: image-processing

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Image Enhancement Algorithm and its Application in Image Defogging

  • Jun Cao
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.465-473
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    • 2023
  • An image enhancement algorithm and image defogging method are studied in this paper. The formation of fog and the characteristics of fog image are analyzed, and the fog image is preprocessed by histogram equalization method; then the additive white noise is removed by foggy image attenuation model, the atmospheric scattering physical model is constructed, the image detail characteristics are enhanced by image enhancement method, and the visual effect of defogging image is enhanced by guided filtering method. The proposed method has a good defogging effect on the image. When the number of training iterations is 3,000, the peak signal-to-noise ratio of the proposed method is 43.29 dB and the image structure similarity is 0.9616, indicating excellent image defogging effect.

An Adaptive Image Enhancement Algorithms Using Saturation Improvement (채도 향상을 이용한 적응형 화질 개선 알고리듬)

  • Jo, Young-Sim;Yun, Jong-Ho;Park, Jin-Sung;Choi, Myung-Ryul
    • Journal of Korea Multimedia Society
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    • v.9 no.11
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    • pp.1455-1464
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    • 2006
  • In this paper, we propose an adaptive image enhancement algorithm. The proposed algorithm is classified with the MIE technique for intensity enhancement of input image and MSE techniques for saturation enhancement. The MIE technique is proposed to control the gamut mapping problem and a sudden change in image-brightness while Luminance signal is processing, The MSE techniques are proposed to control de-saturation or over-saturation while chrominance signal is processing. The proposed algorithm is focused on processing preference color for human vision in order to generate better image quality than the algorithms focused on processing uniformly to whole images, This algorithm can be applied to a monitor, TV and other display devices for high quality image.

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Implementation of Digital Image Processing for Coastline Extraction from Synthetic Aperture Radar Imagery

  • Lee, Dong-Cheon;Seo, Su-Young;Lee, Im-Pyeong;Kwon, Jay-Hyoun;Tuell, Grady H.
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.6_1
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    • pp.517-528
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    • 2007
  • Extraction of the coastal boundary is important because the boundary serves as a reference in the demarcation of maritime zones such as territorial sea, contiguous zone, and exclusive economic zone. Accurate nautical charts also depend on well established, accurate, consistent, and current coastline delineation. However, to identify the precise location of the coastal boundary is a difficult task due to tidal and wave motions. This paper presents an efficient way to extract coastlines by applying digital image processing techniques to Synthetic Aperture Radar (SAR) imagery. Over the past few years, satellite-based SAR and high resolution airborne SAR images have become available, and SAR has been evaluated as a new mapping technology. Using remotely sensed data gives benefits in several aspects, especially SAR is largely unaffected by weather constraints, is operational at night time over a large area, and provides high contrast between water and land areas. Various image processing techniques including region growing, texture-based image segmentation, local entropy method, and refinement with image pyramid were implemented to extract the coastline in this study. Finally, the results were compared with existing coastline data derived from aerial photographs.

Study on the Content Development of Mobile AR_HMD through a Real Time 360 Image Processing. (360° 실시간 영상처리를 통한 모바일 AR_HMD 콘텐츠 개발을 위한 연구)

  • Lee, Changhyun;Kim, Youngseop;Kim, Yeonmin;Park, Inho;Choi, JaeHak;Lee, Yonghwan;Han, Woori
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.2
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    • pp.66-69
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    • 2016
  • Recently, augmented reality and virtual reality in the ICT sector have been highlighted. So also interested in related HMD areas to facilitate contact with the VR content is being attend. This paper proposes a method for implementing to the virtual reality through the mobile HMD device with the real time 360 image. This system is required the real time 360 image streaming server configuration and image processing for augmented reality and virtual reality. The configuration of the streaming server is configured the DB server to store images and the relay server that can relay images to other devices. Augmented image processing module is composed based on markerless tracking, and there are four modules that are recognition, tracking, detecting and learning module. Also, the purpose of this paper is shown the augmented 360 image processing through the Mobile HMD.

Car detection area segmentation using deep learning system

  • Dong-Jin Kwon;Sang-hoon Lee
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.182-189
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    • 2023
  • A recently research, object detection and segmentation have emerged as crucial technologies widely utilized in various fields such as autonomous driving systems, surveillance and image editing. This paper proposes a program that utilizes the QT framework to perform real-time object detection and precise instance segmentation by integrating YOLO(You Only Look Once) and Mask R CNN. This system provides users with a diverse image editing environment, offering features such as selecting specific modes, drawing masks, inspecting detailed image information and employing various image processing techniques, including those based on deep learning. The program advantage the efficiency of YOLO to enable fast and accurate object detection, providing information about bounding boxes. Additionally, it performs precise segmentation using the functionalities of Mask R CNN, allowing users to accurately distinguish and edit objects within images. The QT interface ensures an intuitive and user-friendly environment for program control and enhancing accessibility. Through experiments and evaluations, our proposed system has been demonstrated to be effective in various scenarios. This program provides convenience and powerful image processing and editing capabilities to both beginners and experts, smoothly integrating computer vision technology. This paper contributes to the growth of the computer vision application field and showing the potential to integrate various image processing algorithms on a user-friendly platform

Hardware Software Co-Simulation of the Multiple Image Encryption Technique Using the Xilinx System Generator

  • Panduranga, H.T.;Naveen, Kumar S.K.;Sharath, Kumar H.S.
    • Journal of Information Processing Systems
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    • v.9 no.3
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    • pp.499-510
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    • 2013
  • Hardware-Software co-simulation of a multiple image encryption technique shall be described in this paper. Our proposed multiple image encryption technique is based on the Latin Square Image Cipher (LSIC). First, a carrier image that is based on the Latin Square is generated by using 256-bits of length key. The XOR operation is applied between an input image and the Latin Square Image to generate an encrypted image. Then, the XOR operation is applied between the encrypted image and the second input image to encrypt the second image. This process is continues until the nth input image is encrypted. We achieved hardware co-simulation of the proposed multiple image encryption technique by using the Xilinx System Generator (XSG). This encryption technique is modeled using Simulink and XSG Block set and synthesized onto Virtex 2 pro FPGA device. We validated our proposed technique by using the hardware software co-simulation method.

Development of Real Time and Robust Feature Extraction Algorithm of Watermelon for Tele-robotic Operation (원격 로봇작업을 위한 실시간 수박 형상 추출 알고리즘)

  • Kim, S.C.;Hwang, H.
    • Journal of Biosystems Engineering
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    • v.29 no.1
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    • pp.71-78
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    • 2004
  • Real time and robust algorithm to extract the features of watermelon was developed from the remotely transmitted image of the watermelon. Features of the watermelon at the cultivation site such as size and shape including position are crucial to the successful tole-robotic operation and development of the cultivation data base. Algorithm was developed based on the concept of task sharing between the computer and the operator utilizing man-computer interface. Task sharing was performed based on the functional characteristics of human and computer. Identifying watermelon from the image transmitted from the cultivation site is very difficult because of the variable light condition and the complex image contents such as soil, mulching vinyl, straws on the ground, irregular leaves and stems. Utilizing operator's teaching through the touch screen mounted on the image monitor, the complex time consuming image processing process and instability of processing results in the watermelon identification has been avoided. Color and brightness characteristics were analyzed from the image area specified by the operator's teaching. Watermelon segmentation was performed using the brightness and color distribution of the specified imae processing area. Modified general Hough transform was developed to extract the shape, major and minor axes, and the position, of the watermelon. It took less than 100 msec of the image processing time, and was a lot faster than conventional approach. The proposed method showed the robustness and practicability in identifying watermelon from the wireless transmitted color image of the cultivation site.

Improvement of Satellite Image Value-Added Processing System and Performance Evaluation (위성영상 부가처리시스템(VAPS) 개선 및 성능평가)

  • Lee, Kwangjae;Kim, Eunseon;Moon, Jungye;Kim, Younsoo
    • Aerospace Engineering and Technology
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    • v.13 no.1
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    • pp.174-183
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    • 2014
  • The Value-Added Processing System(VAPS) was developed for post-processing the KOMPSAT imagery. Recently software version and hardware specification of VAPS were changed for improving the VAPS performance. The purpose of this study is to describe about the improvement of existing VAPS(ver.1.0) and systematically evaluate the performance of the improved VAPS(ver.2.0). To this end, test-bed areas in South and North Korea were selected and then image processing tests were conducted using KOMPSAT-2 and KOMPSAT-3 imagery in both areas. In conclusion, VAPS(ver.2.0) had an ability to generate the high level products like ortho images and mosaic images. Image processing time using the Graphic Processing Unit(GPU) on ver.2.0 was enhanced up to 10 times than ver.1.0.

Detection of Subsurface Defects in Metal Materials Using Infrared Thermography; Image Processing and Finite Element Modeling

  • Ranjit, Shrestha;Kim, Won Tae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.34 no.2
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    • pp.128-134
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    • 2014
  • Infrared thermography is an emerging approach to non-contact, non-intrusive, and non-destructive inspection of various solid materials such as metals, composites, and semiconductors for industrial and research interests. In this study, data processing was applied to infrared thermography measurements to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, raw images were often not appropriate. Thus, various data analysis methods were used at the pre-processing and processing levels in data processing programs for quantitative analysis of defect detection and characterization; these increased the infrared non-destructive testing capabilities since subtle defects signature became apparent. A 3D finite element simulation was performed to verify and analyze the data obtained from both the experiment and the image processing techniques.