• 제목/요약/키워드: color images

검색결과 2,708건 처리시간 0.148초

Evaluation of Bone Change by Digital Subtraction Radiography after Implantation of Tooth Ash-plaster Mixture (치아회분과 석고혼합제제 매식후 Digital Subtraction Radiography에 의한 골량 변화의 평가)

  • Kim Jae-Duk;Kim Kwang-Won;Cho Yaung-Gon;Kim Dong-Kie;Choi Eui-Hwan
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • 제29권2호
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    • pp.423-433
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    • 1999
  • Purpose : To assess the methods for the clinical evaluation of the longitudinal bone changes after implantation of tooth ash-plaster mixture into the defect area of human jaws. Materials and methods : Tooth ash-plaster mixtures were implanted into the defects of 8 human jaws. 48 intraoral radiograms taken with copper step wedge as reference at soon, 1st, 2nd, 4th, and 6th week after implantation of mixture were used. X-ray taking was standardized by using Rinn XCP device customized directly to the individual dentition with resin bite block. The images inputted by Quick scanner were digitized and analyzed by NIH image program. Cu­equivalent values were measured at the implanted sites from the periodic digital images. Analysis was performed by the bidirectional subtraction with color enhancement and the surface plot of resliced contiguous image. The obtained results by the two methods were compared with Cu­equivalent value changes. Results : The average determination coefficient of Cu-equivalent equations was 0.9988 and the coefficient of variation of measured Cu values ranged from 0.08~0.10. The coefficient of variation of Cu-equivalent values measured at the areas of the mixture and the bone by the conversion equation ranged from 0.06 ~0.09. The analyzed results by the bidirectional subtraction with color enhancement were coincident with the changes of Cu-equivalent values. The surface plot of the resliced contiguous image showed the three dimensional view of the longitudinal bone changes on one image and also coincident with Cu-equivalent value changes after implantation. Conclusion : The bidirectional subtraction with color enhancement and the surface plot of the resliced contiguous image was very effective and reasonable to analyze clinically and qualitatively the longitudinal bone change. These methods are expected to be applicable to the non-destructive test in other fields.

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Achievement of Color Constancy by Eigenvector (고유벡터에 의한 색 일관성의 달성)

  • Kim, Dal-Hyoun;Bak, Jong-Cheon;Jung, Seok-Ju;Kim, Kyung-Ah;Cha, Eun-Jong;Jun, Byoung-Min
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제10권5호
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    • pp.972-978
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    • 2009
  • In order to achieve color constancy, this paper proposes a method that can detect an invariant direction that affects formation of an intrinsic image significantly, using eigenvector in the $\chi$-chromaticity space. Firstly, image is converted into datum in the $\chi$-chromaticity space which was suggested by Finlayson et al. Secondly, it removes datum, like noises, with low probabilities that may affect an invariant direction. Thirdly, so as to detect the invariant direction that is consistent with a principal direction, the eigenvector corresponding to the largest eigenvalue is calculated from datum extracted above. Finally, an intrinsic image is acquired by recovering datum with the detected invariant direction. Test images were used as parts of the image data presented by Barnard et al., and detection performance of invariant direction was compared with that of entropy minimization method. The results of experiment showed that our method detected constant invariant direction since the proposed method had lower standard deviation than the entropy method, and was over three times faster than the compared method in the aspect of detection speed.

An Epipolar Rectification for Object Segmentation (객체분할을 위한 에피폴라 Rectification)

  • Jeong, Seung-Do;Kang, Sung-Suk;CHo, Jung-Won;Choi, Byung-Uk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제29권1C호
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    • pp.83-91
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    • 2004
  • An epipolar rectification is the process of transforming the epipolar geometry of a pair of images into a canonical form. This is accomplished by applying a homography to each image that maps the epipole to a predetermined point. In this process, rectified images transformed by homographies must be satisfied with the epipolar constraint. These homographies are not unique, however, we find out homographies that are suited to system's purpose by means of an additive constraint. Since the rectified image pair be a stereo image pair, we are able to find the disparity efficiently. Therefore, we are able to estimate the three-dimensional information of objects within an image and apply this information to object segmentation. This paper proposes a rectification method for object segmentation and applies the rectification result to the object segmentation. Using color and relative continuity of disparity for the object segmentation, the drawbacks of previous segmentation method, which are that the object is segmented to several region because of having different color information or another object is merged into one because of having similar color information, are complemented. Experimental result shows that the disparity of result image of proposed rectification method have continuity about unique object. Therefore we have confirmed that our rectification method is suitable to the object segmentation.

Deep Learning based Color Restoration of Corrupted Black and White Facial Photos (딥러닝 기반 손상된 흑백 얼굴 사진 컬러 복원)

  • Woo, Shin Jae;Kim, Jong-Hyun;Lee, Jung;Song, Chang-Germ;Kim, Sun-Jeong
    • Journal of the Korea Computer Graphics Society
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    • 제24권2호
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    • pp.1-9
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    • 2018
  • In this paper, we propose a method to restore corrupted black and white facial images to color. Previous studies have shown that when coloring damaged black and white photographs, such as old ID photographs, the area around the damaged area is often incorrectly colored. To solve this problem, this paper proposes a method of restoring the damaged area of input photo first and then performing colorization based on the result. The proposed method consists of two steps: BEGAN (Boundary Equivalent Generative Adversarial Networks) model based restoration and CNN (Convolutional Neural Network) based coloring. Our method uses the BEGAN model, which enables a clearer and higher resolution image restoration than the existing methods using the DCGAN (Deep Convolutional Generative Adversarial Networks) model for image restoration, and performs colorization based on the restored black and white image. Finally, we confirmed that the experimental results of various types of facial images and masks can show realistic color restoration results in many cases compared with the previous studies.

Detail Enhancement by Spatial Gamut Mapping Based on Local Contrast Compensation (지역적 대비를 보상하는 색역 사상을 통한 상세정보 향상)

  • Song, In-Yong;Ha, Ho-Gun;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • 제49권4호
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    • pp.58-66
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    • 2012
  • Currently many devices reproduce electronic images in the various ways. However, the color that is reproduced in any device is different from the original color due to the differences in the gamut between devices. A recent trend in gamut mapping algorithms is the use of spatial information to compute the color transformation of pixels from the input to the output gamut. However, these techniques share the problem of preserving details, and avoiding halos, and hue shift. In this paper, spatial gamut mapping for preserving the details of the input image is proposed. Our approach improves visibility of detail that is not effectively represented with conventional spatial gamut mapping. In proposed method, initially, we gamut map the input image using gamut clipping and obtain a detail layer for both the input and the gamut mapped images. Next, we calculate the difference between the two detail layers, obtaining the details of the out of gamut region. Finally, we add the details of out of gamut region to the gamut mapped image. Since the resulting image has out of gamut colors, we obtain resulting image of proposed method by using a gamut clipping method. Consequently, the printed output image was more consistent with the corresponding monitor image.

A Fast and Accurate Face Detection and Tracking Method by using Depth Information and color information (깊이정보와 컬러정보를 이용한 고속 고정밀 얼굴검출 및 추적 방법)

  • Kim, Woo-Youl;Seo, Young-Ho;Kim, Dong-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • 제16권9호
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    • pp.1825-1838
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    • 2012
  • This paper proposes a fast face detection and tracking method which uses depth images as well as RGB images. It consists of the face detection procedure and the face tracking procedure. The face detection method basically uses an existing method, Adaboost, but it reduces the size of the search area by using the depth information and skin color. The proposed face tracking method uses a template matching technique and incorporates an early-termination scheme to reduce the execution time further. The results from implementing and experimenting the proposed methods showed that the proposed face detection method takes only about 39% of the execution time of the existing method. The proposed tracking method takes only 2.48ms per frame. For the exactness, the proposed detection method and previous method showed a same detection ratio but in the error ratio, which is about 0.66%, the proposed method showed considerably improved performance. In all the cases except a special one, the tracking error ratio is as low as about 1%. Therefore, we expect the proposed face detection and tracking methods can be used individually or in combined for many applications that need fast execution and exact detection or tracking.

A Tracking Algorithm to Certain People Using Recognition of Face and Cloth Color and Motion Analysis with Moving Energy in CCTV (폐쇄회로 카메라에서 운동에너지를 이용한 모션인식과 의상색상 및 얼굴인식을 통한 특정인 추적 알고리즘)

  • Lee, In-Jung
    • The KIPS Transactions:PartB
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    • 제15B권3호
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    • pp.197-204
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    • 2008
  • It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

Performance Comparison of the Recognition Methods of a Touched Area on a Touch-Screen Panel for Embedded Systems (임베디드 시스템을 위한 터치스크린 패널의 터치 영역 인식 기법의 성능 비교)

  • Oh, Sam-Kweon;Park, Geun-Duk;Kim, Byoung-Kuk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제10권9호
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    • pp.2334-2339
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    • 2009
  • In case of an embedded system having an LCD panel with touch-screen capability, various figures such as rectangles, pentagons, circles, and arrows are frequently used for the delivery of user-input commands. In such a case, it is necessary to have an algorithm that can recognize whether a touched location is within a figure on which a specific user-input command is assigned. Such algorithms, however, impose a considerable amount of overhead for embedded systems with restricted amount of computing resources. This paper first describes a method for initializing and driving a touch-screen LCD and a coordinate-calibration method that converts touch-screen coordinates into LCD panel coordinates. Then it introduces methods that can be used for recognizing touched areas of rectangles, many-sided figures like pentagons, and circles; they are a range checking method for rectangles, a crossing number checking method for many-sided figures, a distance measurement method for circles, and a color comparison method that can be applied to all figures. In order to evaluate the performance of these methods, we implement two-dimensional graphics functions for drawing figures like triangles, rectangles, circles, and images. Then, we draw such figures and measures times spent for the touched-area recognition of these figures. Measurements show that the range checking is the most suitable method for rectangles, the distance measurement for circles, and the color comparison for many-sided figures and images.

Super Resolution Algorithm Based on Edge Map Interpolation and Improved Fast Back Projection Method in Mobile Devices (모바일 환경을 위해 에지맵 보간과 개선된 고속 Back Projection 기법을 이용한 Super Resolution 알고리즘)

  • Lee, Doo-Hee;Park, Dae-Hyun;Kim, Yoon
    • KIPS Transactions on Software and Data Engineering
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    • 제1권2호
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    • pp.103-108
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    • 2012
  • Recently, as the prevalence of high-performance mobile devices and the application of the multimedia content are expanded, Super Resolution (SR) technique which reconstructs low resolution images to high resolution images is becoming important. And in the mobile devices, the development of the SR algorithm considering the operation quantity or memory is required because of using the restricted resources. In this paper, we propose a new single frame fast SR technique suitable for mobile devices. In order to prevent color distortion, we change RGB color domain to HSV color domain and process the brightness information V (Value) considering the characteristics of human visual perception. First, the low resolution image is enlarged by the improved fast back projection considering the noise elimination. And at the same time, the reliable edge map is extracted by using the LoG (Laplacian of Gaussian) filtering. Finally, the high definition picture is reconstructed by using the edge information and the improved back projection result. The proposed technique removes effectually the unnatural artefact which is generated during the super resolution restoration, and the edge information which can be lost is amended and emphasized. The experimental results indicate that the proposed algorithm provides better performance than conventional back projection and interpolation methods.

Development the Geostationary Ocean Color Imager (GOCI) Data Processing System (GDPS) (정지궤도 해색탑재체(GOCI) 해양자료처리시스템(GDPS)의 개발)

  • Han, Hee-Jeong;Ryu, Joo-Hyung;Ahn, Yu-Hwan
    • Korean Journal of Remote Sensing
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    • 제26권2호
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    • pp.239-249
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    • 2010
  • The Geostationary Ocean Color Imager (GOCI) data-processing system (GDPS), which is a software system for satellite data processing and analysis of the first geostationary ocean color observation satellite, has been developed concurrently with the development of th satellite. The GDPS has functions to generate level 2 and 3 oceanographic analytical data, from level 1B data that comprise the total radiance information, by programming a specialized atmospheric algorithm and oceanic analytical algorithms to the software module. The GDPS will be a multiversion system not only as a standard Korea Ocean Satellite Center(KOSC) operational system, but also as a basic GOCI data-processing system for researchers and other users. Additionally, the GDPS will be used to make the GOCI images available for distribution by satellite network, to calculate the lookup table for radiometric calibration coefficients, to divide/mosaic several region images, to analyze time-series satellite data. the developed GDPS system has satisfied the user requirement to complete data production within 30 minutes. This system is expected to be able to be an excellent tool for monitoring both long-term and short-term changes of ocean environmental characteristics.