• Title/Summary/Keyword: shadow detection

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people counting system using single camera (카메라영상을 이용한 people counting system)

  • Jeong, Ha-Wook;Chang, Hyung-Jin;Baek, Young-Min;Kim, Soo-Wan;Choi, Jin-Young
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.172-174
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    • 2009
  • This paper describes an implementation method for the 'People Counting System' which detects and tracks moving people using a fixed single camera. This system proposes the method of improving performances by compensating weakness of existing algorithm. For increasing effect of detection, this system uses Single Gaussian Background Modeling which is more robust at noise and has adaptiveness. It minimizes unnecessarily detected area that is a limitation of the detecting method by using the background differences. And this system prevents additional detecting problems by removing shadow. Also, This system solves the problems of segmentation and union of people by using a new method. This method can work appropriately, if the angle of camera would not strictly vertical or the direction of shadow were lopsided. Also, by using integration System, it can solve a number of special cases as many as possible. For example, if the system fails to tracking, it will detect the object again and will make it possible to count moving people.

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Pedestrians Action Interpretation based on CUDA for Traffic Signal Control (교통신호제어를 위한 CUDA기반 보행자 행동판단)

  • Lee, Hong-Chang;Rhee, Sang-Yong;Kim, Young-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.5
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    • pp.631-637
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    • 2010
  • In this paper, We propose a method of motion interpretation of pedestrian for active traffic signal control. We detect pedestrian object in a movie of crosswalk area by using the code book method and acquire contour information. To do this stage fast, we use parallel processing based on CUDA (Compute Unified Device Architecture). And we remove shadow which causes shape distortion of objects. Shadow removed object is judged by using the hilbert scan distance whether to human or noise. If the objects are judged as a human, we analyze pedestrian objects' motion, face area feature, waiting time to decide that they have intetion to across a crosswalk for pdestrians. Traffic signal can be controlled after judgement.

Context-aware Video Surveillance System

  • An, Tae-Ki;Kim, Moon-Hyun
    • Journal of Electrical Engineering and Technology
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    • v.7 no.1
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    • pp.115-123
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    • 2012
  • A video analysis system used to detect events in video streams generally has several processes, including object detection, object trajectories analysis, and recognition of the trajectories by comparison with an a priori trained model. However, these processes do not work well in a complex environment that has many occlusions, mirror effects, and/or shadow effects. We propose a new approach to a context-aware video surveillance system to detect predefined contexts in video streams. The proposed system consists of two modules: a feature extractor and a context recognizer. The feature extractor calculates the moving energy that represents the amount of moving objects in a video stream and the stationary energy that represents the amount of still objects in a video stream. We represent situations and events as motion changes and stationary energy in video streams. The context recognizer determines whether predefined contexts are included in video streams using the extracted moving and stationary energies from a feature extractor. To train each context model and recognize predefined contexts in video streams, we propose and use a new ensemble classifier based on the AdaBoost algorithm, DAdaBoost, which is one of the most famous ensemble classifier algorithms. Our proposed approach is expected to be a robust method in more complex environments that have a mirror effect and/or a shadow effect.

Image-based Extraction of Histogram Index for Concrete Crack Analysis

  • Kim, Bubryur;Lee, Dong-Eun
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.912-919
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    • 2022
  • The study is an image-based assessment that uses image processing techniques to determine the condition of concrete with surface cracks. The preparations of the dataset include resizing and image filtering to ensure statistical homogeneity and noise reduction. The image dataset is then segmented, making it more suited for extracting important features and easier to evaluate. The image is transformed into grayscale which removes the hue and saturation but retains the luminance. To create a clean edge map, the edge detection process is utilized to extract the major edge features of the image. The Otsu method is used to minimize intraclass variation between black and white pixels. Additionally, the median filter was employed to reduce noise while keeping the borders of the image. Image processing techniques are used to enhance the significant features of the concrete image, especially the defects. In this study, the tonal zones of the histogram and its properties are used to analyze the condition of the concrete. By examining the histogram, the viewer will be able to determine the information on the image through the number of pixels associated and each tonal characteristic on a graph. The features of the five tonal zones of the histogram which implies the qualities of the concrete image may be evaluated based on the quality of the contrast, brightness, highlights, shadow spikes, or the condition of the shadow region that corresponds to the foreground.

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SiC(3C)/Si Photodetector (SiC(3C)/Si 수광소자)

  • 박국상;남기석;김정윤
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.9 no.2
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    • pp.212-216
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    • 1999
  • SiC(3C) photodiodes (PDs) were fabricated on p-type Si(111) substrates using chemical vapor deposition (CVD) technique by pyrolyzing tetramethylsilane (TMS) with H2 carrier gas. Electrical properties of SiC(3C) were investigated by Hall measurement and current-voltage (I-V) characteristics. SiC(3C) layers exhibited n-type conductivity. Ohmic contact was formed by thermal evaporation Al metal through a shadow-mask. The optical gain (Gop) of the SiC(3C)/Si PD was measured as a function of the incident wavelength. For the analysis of the photovoltaic detection of the Sic(3C) n/p PD, the spectral response (SR) has calculated by using the electrical parameters of the SiC(3C) layer and the geometric structure of the PD. The peak response calculated for properly chosen parameters was about 0.75 near 550 nm. We expect a good photoresponse in the SiC(3C) heterostructure for the wavelength range of 400~600 nm. The SiC(3C) photodiode can detect blue and near ultraviolet (UV) radiation.

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U-Net Cloud Detection for the SPARCS Cloud Dataset from Landsat 8 Images (Landsat 8 기반 SPARCS 데이터셋을 이용한 U-Net 구름탐지)

  • Kang, Jonggu;Kim, Geunah;Jeong, Yemin;Kim, Seoyeon;Youn, Youjeong;Cho, Soobin;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1149-1161
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    • 2021
  • With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

Automatic Coin Calculation System using Circular Hough Transform and Post-processing Techniques (원형 Hough 변환 및 후처리기법을 이용한 동전 자동 계산 시스템)

  • Chae, S.;Jun, Kyungkoo
    • Journal of Korea Multimedia Society
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    • v.17 no.4
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    • pp.413-419
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    • 2014
  • In this paper, we develop an automatic coin calculation system by using digital image processing. Existing schemes have the problem that is not able to exclude non-circular shape from the calculation. We propose a method to detect only coins which have circular form by applying the circular Hough transform(CHT). However, the CHT has the drawback that detects multiple circles even for just one coin because of shadow noise, the patterns on coins, and non-circular edge detection. We propose a post processing algorithm to overcome these limitations. The proposed system was implemented and successfully calculated the coin amount in the case that non-circular objects are mixed with coins.

Lane Detection for Parking Violation Assessments

  • Kim, A-Ram;Rhee, Sang-Yong;Jang, Hyeon-Woong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.1
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    • pp.13-20
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    • 2016
  • In this study, we propose a method to regulate parking violations using computer vision technology. A still color image of the parked vehicle under question is obtained by a camera mounted on enforcement vehicles. The acquired image is preprocessed through a morphological algorithm and binarized. The vehicle's shadows are detected from the binarized image, and lanes are identified using the information from the yellow parking lines that are drawn on the load. Whether parking is illegal is determined by the conformity of the lanes and the vehicle's shadow.

Automated Detection of Pulmonary Nodules in Chest Radiography Using Template Matching (단순흉부영상의 Template-Matching을 이용한 폐 결절 자동 추출)

  • 류지연;이경일;오명진;장정란;이배호
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.335-338
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    • 2002
  • This paper proposes some technical approaches for automatic detection of pulmonary nodules in chest X-ray images. We applied threshold technique for the lung field segmentation and extended the lung field by using morphological methods. A template matching technique was employed for automatic detecting nodules in lung area. Genetic algorithm(GA) was used in template matching(TM) to select a matched image from various reference patterns(simulated typical nodules). We eliminated the false-positive candidates by using histograms and contrasts. We used standard databases published by Japanese Society of Radiological Technology (JSRT) for correct results. Also we employ two-dimensional Gaussian distribution for some reference images because the shadow of lung nodules in radiogram generally shows the distributions. Nodules of about 89% were correctly detected by our scheme. The simulation results show that it is an effective method to indicate lesions on chest radiograms.

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Skewed Angle Detection in Text Images Using Orthogonal Angle View

  • Chin, Seong-Ah;Choo, Moon-Won
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.62-65
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    • 2000
  • In this paper we propose skewed angle detection methods for images that contain text that is not aligned horizontally. In most images text areas are aligned along the horizontal axis, however there are many occasions when the text may be at a skewed angle (denoted by 0 < θπ). In the work described, we adapt the Hough transform, Shadow and Threshold Projection methods to detect the skewed angle of text in an input image using the orthogonal angle view property. The results of this method are a primary text skewed angle, which allows us to rotate the original input image into an image with horizontally aligned text. This utilizes document image processing prior to the recognition stage.

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