• Title/Summary/Keyword: Local Image Processing

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Lane Detection and Tracking Algorithm based on Corner Detection and Tracking (모서리 검출과 추적을 이용한 차선 감지 및 추적 알고리즘)

  • Kim, Seong-Do;Park, Ji-Hun;Park, Joon-Sang
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.10 no.3
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    • pp.64-73
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    • 2011
  • This paper presents an algorithm for tracking lanes on the road based on corner detection techniques. The proposed algorithm shows high accuracy regardless of lane divider types, eg, solid line, dashed line, etc, and thus is of advantage to city streets and local roads where various types of lane dividers are used. A set of experiments was conducted on real roads with various types of lane dividers and results show an extract ratio over 87% in average.

Specialized VLSI System Design for the Generalized Hough Transform (일반화된 Hough 변환을 위한 특수 목적 VLSI 시스템 설계에 관한 연구)

  • 채옥삼;이정헌
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.3
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    • pp.66-76
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    • 1995
  • In this research, a mesh connected VLSI structure is proposed for the real time computation of the generalized Hough transform(GHT). The purpose of the research is to design a generalized Hough transformer that can be realized as a single chip processor. The GHT has been modified to yield a highly parallel structure consisting of simple processing elements(PEs) and communication networks. In the proposed structure, the GHT can be computed by first assigning an image pixel to a PE and performing shift and add operations. The result of the CAD circuit simulation shows that it can be computed in the time proportional to the number of pixels in the pattern. In addition to the Hough transformer, the peak detector has been designed to reduce 1)the number of the I/O operations between the transformer and the host computer and 2) the host computer's burden for peak detection by transmitting only the local peaks detected from the transformed accumulator. It is expected that the proposed single chip Hough transformer with peak detector makes a fast and inexpensive edge based object recognition systems possible for many industrial and military applications.

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Vision based Monitoring System for Safety in Railway Station (철도역사 안전을 위한 비전기반 승강장 모니터링 시스템)

  • Oh, Seh-Chan;Park, Sung-Hyuk;Lee, Chang-Mu
    • Proceedings of the KSR Conference
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    • 2007.05a
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    • pp.953-958
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    • 2007
  • Passenger safety is a primary concern of railway system but, it has been urgent issue that dozens of people are killed every year when they are fallen from train platforms. In this paper, we propose a vision based monitoring system for railway station platform. The system immediately perceives dangerous factors of passengers on the platform by using image processing technology. To monitor almost entire length of the track line in the platform, we use several video cameras. Each camera conducts surveillance its own preset monitoring area whether human or dangerous object was fallen in the area. Moreover, to deal with the accident immediately, the system provides local station, central control room employees and train driver with the video information about the accident situation including alarm message. This paper introduces the system overview and detection process with experimental results. According to the results, we expect the proposed system will play a key role for establishing highly intelligent monitoring system in railway.

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Robust Real-time Night Visibility Enhancement for Environmental Change using Haze Removal Method (안개제거 방법을 이용한 환경변화에 강인한 실시간 야간 가시성 향상)

  • Lee, Jae-Won;Hong, Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.18 no.3
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    • pp.339-348
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    • 2015
  • In this paper, we propose improved night visibility enhancement algorithm based on haze removal method. The proposed method uses new haze removal method in place of the conventional methods. Our night visibility enhancement method is very good and faster than traditional methods. This method also uses additionally local histogram equalization for sharpening the enhanced image. Our method can be applied to any application that uses a visible light camera, and it is appropriate to apply a black box, vehicle camera, and cell phone camera, since it is possible that real-time processing.

An Investigation on Heat transfer Characteristics of Inclined Wall Attaching Offest jet (경사진 벽부착 제트의 열전달 특성에 대한 연구)

  • 심재경
    • Journal of Advanced Marine Engineering and Technology
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    • v.22 no.2
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    • pp.200-209
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    • 1998
  • Experiments have been conducted to determine heat transfer characteristics for a two-dimen-sional turbulent wall attaching offset jet at different oblique angles to a flat surface. The local Nusselt number distributions were measured using liquid crystal as a temperature sensor. Wall static pressure coefficient profiles were measured at the Reynolds number Re 53200(based on the nozzle width, D) the offset ratio H/D from 2.5 to 10 and the oblique angle a from $0^{\circ}$, to $40^{\circ}$ It is observed that the maximum Nusselt number point occurs slightly upstream of time-averaged reattachment point for all oblique angles. The correlations between the maximum Nusselt number and Reynolds number offset ration and oblique angle are presented.

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Development of High-speed Tunnel Fire Detection Algorithm Using the Global and Local Features (영상 처리 기법을 이용한 터널 내 화재의 고속 탐지 기법의 개발)

  • Lee, Byoung-Moo;Han, Dong-Il
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.305-306
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    • 2006
  • To avoid the large scale of damage when fire occurs in the tunnel, it is necessary to have a system to minimize the damage, and early discovery of the problem. In this paper, we have proposed algorithm using the image processing, which is the high-speed detection for the occurrence of fire or smoke in the tunnel. The fire detection is different to the forest fire detection as there are elements such as car and tunnel lightings and other variety of elements different from the forest environment. Therefore, an indigenous algorithm should be developed.The two algorithms proposed in this paper, are able to complement with each other and also they can detect the exact position, at the earlier stay of detection. In addition, by comparing properties of each algorithm throughout this experiment, we have proved the propriety of algorithm.

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Hierarchical Behavior Control of Mobile Robot Based on Space & Time Sensor Fusion(STSF)

  • Han, Ho-Tack
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.4
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    • pp.314-320
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    • 2006
  • Navigation in environments that are densely cluttered with obstacles is still a challenge for Autonomous Ground Vehicles (AGVs), especially when the configuration of obstacles is not known a priori. Reactive local navigation schemes that tightly couple the robot actions to the sensor information have proved to be effective in these environments, and because of the environmental uncertainties, STSF(Space and Time Sensor Fusion)-based fuzzy behavior systems have been proposed. Realization of autonomous behavior in mobile robots, using STSF control based on spatial data fusion, requires formulation of rules which are collectively responsible for necessary levels of intelligence. This collection of rules can be conveniently decomposed and efficiently implemented as a hierarchy of fuzzy-behaviors. This paper describes how this can be done using a behavior-based architecture. The approach is motivated by ethological models which suggest hierarchical organizations of behavior. Experimental results show that the proposed method can smoothly and effectively guide a robot through cluttered environments such as dense forests.

Heterogeneous Parallel Architecture for Face Detection Enhancement

  • Albssami, Aishah;Sharaf, Sanaa
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.193-198
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    • 2022
  • Face Detection is one of the most important aspects of image processing, it considers a time-consuming problem in real-time applications such as surveillance systems, face recognition systems, attendance system and many. At present, commodity hardware is getting more and more heterogeneity in terms of architectures such as GPU and MIC co-processors. Utilizing those co-processors along with the existing traditional CPUs gives the algorithm a better chance to make use of both architectures to achieve faster implementations. This paper presents a hybrid implementation of the face detection based on the local binary pattern (LBP) algorithm that is deployed on both traditional CPU and MIC co-processor to enhance the speed of the LBP algorithm. The experimental results show that the proposed implementation achieved improvement in speed by 3X when compared to a single architecture individually.

Wavelet-Based Edge Detection Using Local Histogram Analysis in Images (영상에서 웨이블렛 기반 로컬 히스토그램 분석을 이용한 에지검출)

  • Park, Min-Joon;Kwon, Min-Jun;Kim, Gi-Hun;Shim, Han-Seul;Kim, Dong-Wook;Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.359-371
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    • 2011
  • Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

Reduction of Radiographic Quantum Noise Using Adaptive Weighted Median Filter (적응성 가중메디안 필터를 이용한 방사선 투과영상의 양자 잡음 제거)

  • Lee, Hoo-Min;Nam, Moon-Hyon
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.5
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    • pp.465-473
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    • 2002
  • Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.