• Title/Summary/Keyword: Morphological Image Processing

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Facial Region Tracking by Utilizing Infra-Red and CCD Color Image (CCD 컬러 영상과 적외선 영상을 이용한 얼굴 영역 검출)

  • Kim K. S.;Lee J. W.;Yoon T. H.;Han M. H.;Shin S. W.;Kim I. Y.;Song C. G.
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.9
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    • pp.577-579
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    • 2005
  • In this study, the automatic tracking algorithm tracing a human face is proposed by using YCbCr color coordinated information and its thermal properties expressed in terms of thermal indexes in an infra-red image. The facial candidates are separately estimated in CbCr color and infra-red domain, respectively with applying the morphological image processing operations and the geometrical shape measures for fitting the elliptical features of a human face. The identification of a true face is accomplished by logical 'AND' operation between the refined image in CbCr color and infra-red domain.

Fast Image Pre-processing Algorithms Using SSE Instructions (SSE 명령어를 이용한 영상의 고속 전처리 알고리즘)

  • Park, Eun-Soo;Cui, Xuenan;Kim, Jun-Chul;Im, Yu-Cheong;Kim, Hak-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.2
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    • pp.65-77
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    • 2009
  • This paper proposes fast image processing algorithms using SSE (Streaming SIMD Extensions) instructions. The CPU's supporting SSE instructions have 128bit XMM registers; data included in these registers are processed at the same time with the SIMD (Single Instruction Multiple Data) mode. This paper develops new SIMD image processing algorithms for Mean filter, Sobel horizontal edge detector, and Morphological erosion operation which are most widely used in automated optical inspection systems and compares their processing times. In order to objectively evaluate the processing time, the developed algorithms are compared with OpenCV 1.0 operated in SISD (Single Instruction Single Data) mode, Intel's IPP 5.2 and MIL 8.0 which are fast image processing libraries supporting SIMD mode. The experimental result shows that the proposed algorithms on average are 8 times faster than the SISD mode image processing library and 1.4 times faster than the SIMD fast image processing libraries. The proposed algorithms demonstrate their applicability to practical image processing systems at high speed without commercial image processing libraries or additional hardwares.

A GPU-based Filter Algorithm for Noise Improvement in Realtime Ultrasound Images (실시간 초음파 영상에서 노이즈 개선을 위한 GPU 기반의 필터 알고리즘)

  • Cho, Young-Bok;Woo, Sung-Hee
    • Journal of Digital Contents Society
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    • v.19 no.6
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    • pp.1207-1212
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    • 2018
  • The ultrasound image uses ultrasonic pulses to receive the reflected waves and construct an image necessary for diagnosis. At this time, when the signal becomes weak, noise is generated and a slight difference in brightness occurs. In addition, fluctuation of image due to breathing phenomenon, which is the characteristic of ultrasound image, and change of motion in real time occurs. Such a noise is difficult to recognize and diagnose visually in the analysis process. In this paper, morphological features are automatically extracted by using image processing technique on ultrasound acquired images. In this paper, we implemented a GPU - based fast filter using a cloud big data processing platform for image processing. In applying the GPU - based high - performance filter, the algorithm was run with performance 4.7 times faster than CPU - based and the PSNR was 37.2dB, which is very similar to the original.

VLSI Architecture Design of Reconstruction Filter for Morphological Image Segmentation (형태학적 영상 분할을 위한 재구성 필터의 VLSI 구조 설계)

  • Lee, Sang-Yeol;Chung, Eui-Yoon;Lee, Ho-Young;Kim, Hee-Soo;Ha, Yeong-Ho
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.12
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    • pp.41-50
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    • 1999
  • In this paper, the new VLSI architecture of a reconstruction filter for morphological image segmentation is proposed. The filter, based on the $h_{max}$ operation, simplifies the interior of each region while preserving the boundary information. The proposed architecture adopts a partitioned memory structure and an efficient image scanning strategy to reduce the operations. The proposed memory partitioning scheme makes it possible that every data required for processing can be read from each memory at a time, resulting in parallel data processing. By the extended connectivity consideration, the operation is much decreased because more simplification is achieved in scanning stage. The selective raster scan strategy endows the satisfactory noise removal capability with negligible hardware complexity increase. The proposed architecture is designed using VHDL, and functional evaluation is performed by the CAD tool, Mentor. The experiment results show that the proposed architecture can simplify image profile with less than 18% operations of the conventional method.

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Vehicle Tracking using Euclidean Distance (유클리디안 척도를 이용한 차량 추적)

  • Kim, Gyu-Yeong;Kim, Jae-Ho;Park, Jang-Sik;Kim, Hyun-Tae;Yu, Yun-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1293-1299
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    • 2012
  • In this paper, a real-time vehicle detection and tracking algorithms is proposed. The vehicle detection could be processed using GMM (Gaussian Mixture Model) algorithm and mathematical morphological processing with HD CCTV camera images. The vehicle tracking based on separated vehicle object was performed using Euclidean distance between detected object. In more detail, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the next stage, candidated objects were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations dependent on distance and vehicle type in tunnel. The vehicle tracking performed using Euclidean distance between the objects in the video frames. Through computer simulation using recoded real video signal in tunnel, it is shown that the proposed system works well.

Auto-Segmentation Algorithm For Liver-Vessel From Abdominal MDCT Image Using Morphological Filtering (Morphological Filtering을 이용한 복부 MDCT 영상의 간혈관 자동 추출 알고리즘)

  • Park, Chun-Ja;Ryu, Gang-Min;Park, Jong-Won
    • Annual Conference of KIPS
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    • 2005.05a
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    • pp.819-822
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    • 2005
  • 본 연구는 MDCT 영상을 이용하여 인체의 장기인 간을 추출하고 그 간 내부의 혈관을 추출하는 알고리즘을 제안하였다. 간에는 2개의 주요혈관이 있는데 생체 간 이식 수술시 필수적인 간의 절개 비율 및 간 내의 혈관 모습들을 제공하여 의료진에게 수술 전 혈관 형태에 대한 정확히 정보를 파악하도록 함으로써 혈관의 손상을 최대한으로 줄일 수 있도록 하여 수술 성공률을 높이는데 중요한 역할을 할 수 있다. 간을 이식 할 때 기증자와 수혜자가 동시에 생존하기 위해서는 기증자의 간으 크기가 중요하며 둘다 생존하기 위해서는 기증자는 자신의 간의 35% 이상을 남겨야 하며 수혜자 또한 생존을 위해 자신의 간의 40% 이상에 해당하는 간을 이식 받아야 하는데 간 이식에 있어서 절단 부분을 결정하는데 중요한 중간 정맥을 찾아내어 보여 줌으로써 중간 정맥을 중심으로 3가닥의 굵은 혈관과 주변혈관의 손상을 최소화하고 비율을 잘 맞추어 절단 할 수 있도록 수술하는데 도움을 줄 수 있다. 각 혈관은 원형성과 다양한 각도를 갖는 막대형의 형태를 가지고 있다는 특징을 이용해 morphological filtering을 통해 추출한 후 조합하여 재구성을 하여 혈관의 모습으로 생성해 낼 수 있었다.

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Automated radiation field edge detection in portal image using optimal threshold value (최적 문턱치 설정을 이용한 포탈영상에서의 자동 에지탐지 기법에 관한 연구)

  • 허수진
    • Journal of Biomedical Engineering Research
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    • v.16 no.3
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    • pp.337-344
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    • 1995
  • Because of the high energy of the treatment beam, contrast of portal films is very poor. Many image processing techniques have been applied to the portal images but a significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it may be remedied by separating the treatment field from the background prior to enhancement and uslng only the pixels within the field boundary in the enhancement procedure. A new edge extraction algorithm for accurate extraction of the radiation field boundary from portal Images has been developed for contrast enhancement of portal images. In this paper, portal image segmentation algorithm based on Sobel filtration, labelling processes and morphological thinning has been presented. This algorithm could automatically search the optimal threshold value which is sensitive to the variation of the type and quality of portal images.

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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.

Confocal Microscopy Image Segmentation and Extracting Structural Information for Morphological Change Analysis of Dendritic Spine (수상돌기 소극체의 형태변화 분석을 위한 공초점현미경 영상 분할 및 구조추출)

  • Son, Jeany;Kim, Min-Jeong;Kim, Myoung-Hee
    • Journal of the Korea Society for Simulation
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    • v.17 no.4
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    • pp.167-174
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    • 2008
  • The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

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Characterization of nano-fiber web structures using a morphological image processing

  • Kim, Jooyong;Lee, Jung-Hae
    • Proceedings of the Korean Fiber Society Conference
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    • 2003.10a
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    • pp.100-100
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    • 2003
  • An image processing algorithm has been developed in order to analyze the nanofiber web images obtained from a high magnification microscope. It has been known that precise pore detection on thick webs is extremely difficult mainly due to lack of light uniformity, difficulty of fine focusing and translucency of nanofiber web. The pore detection algorithm developed has been found to show excellent performance in characterizing the porous structure, thus being a promising tool for on-line quality control system under mass production. Since the images obtained from an optical microscope represent only web surface, a scale factor has been introduced to estimate the web structure as a whole. Resulting web structures have been compared to those by mercury porosimetry, especially in pore size distribution. It has been shown that those two structures have a strong correlation, indicating that scaling of a single layer web structure can be an effective way of estimating the structure of thick fiber webs.

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