• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.268-271
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• 2016

In video sequences, foreground object detection being composed of a background model and a background subtraction is an important part of diverse computer vision applications. However, object detection might fail in sudden illumination changes. In this letter, an illumination-robust background detection is proposed to address this problem. The method can provide quick adaption to current illumination condition using two background models with different adaption rates. Since the proposed method is a non-parametric approach, experimental results show that the proposed algorithm outperforms several state-of-art non-parametric approaches and provides low computational cost.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.745-751
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• 2016

A detection algorithm, based on the combined local-global (CLG) optical-flow model and Gaussian pyramid for a moving target appearing against a dynamic background, can compensate for the inadaptability of the classic Horn-Schunck algorithm to illumination changes and reduce the number of needed calculations. Incorporating the hypothesis of gradient conservation into the traditional CLG optical-flow model and combining structure and texture decomposition enable this algorithm to minimize the impact of illumination changes on optical-flow estimates. Further, calculating optical-flow with the Gaussian pyramid by layers and computing optical-flow at other points using an optical-flow iterative with higher gray-level points together reduce the number of calculations required to improve detection efficiency. Finally, this proposed method achieves the detection of a moving target against a dynamic background, according to the background motion vector determined by the displacement and magnitude of the optical-flow. Simulation results indicate that this algorithm, in comparison to the traditional Horn-Schunck optical-flow algorithm, accurately detects a moving target undergoing illumination changes against a dynamic background and simultaneously demonstrates a significant reduction in the number of computations needed to improve detection efficiency.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.91-102
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• 2010

It is very difficult that a previous surveillance system and vehicle detection system find objects on a limited and unstable illumination condition. This paper proposes a robust method of adaptively updating a reference background image for solving problems that are generated by the unstable illumination. The first input image is set up as the reference background image, and is divided into three block categories according to an edge component. Then a block state analysis, which uses a rate of change of the brightness, a stability, a color information, and an edge component on each block, is applied to the input image. On the reference background image, neighbourhood blocks having the same state of a updated block are merged as a block. The proposed method can generate a robust reference background image because it distinguishes a moving object area from an unstable illumination. The proposed method very efficiently updates the reference background image from the point of view of the management and the processing time. In order to demonstrate the superiority of the proposed stable manner in situation that an illumination quickly changes.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.4-162
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• 2001

This paper presents a fuzzy-based method for classification skin color object in a complex background under varying illumination Parameters of fuzzy rule base are generated using a genetic algorithm(GA). The color model is used in the YCbCr color space. We propose a unique fuzzy system in order to accommodate varying background color and illumination condition This fuzzy system approach to skin color classification is discussed along with an overview of YCbCr color space.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.3
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• pp.9-23
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• 1995

To analyze the spray and flame in D.I. diesel engine, the visualizing methods by schlieren photograph and diffused background illumination photograph with high speed camera are applied to optically accessible D.I.diesel engine. Wcaporating spray, spray droplets and brightness flame are taken with high speed camera by visuallizing method in accordance with various suction air temperature and injection time. The spray and flame image on the film was analyzed by image analyzer. The optically accessible D.I. diesel engine had the similar pressure characteristic to the real D.I. diesel engine. Experimental results showed that shadow areas of the evaporating spray were extended at higher suction air temperature, spray droplets had a max. Penetration length and their penetrating patterns were dependent on the surrounding gas temperature, and flame size after ignition was largely governed by the evaporated fuel quantity at ignition point and by the surrounding gas condition due to piston motion.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.6
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• pp.30-40
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• 1995

Optically accessible D. I. diesel engine with a rectangular combustion chamber was constructed to visualize the behaviors of sprays and flames in the combustion camber with the close conditions of pressure and temperature in an actual engine. The behaviors of sprays and flames in the combustion chamber as the operating conditions of this engine were photographed with high speed camera by Diffused Background Illumination Method. With photographs taken by this method, behavior of spray droplets injected into the combustion chamber, ignition points, and flame propagation were observed and analyzed at a time-and space-dependent fashion.

• Convergence Security Journal
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• v.7 no.1
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• pp.1-10
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• 2007

Surveillance system with the fixed field of view generally has an identical background and is easy to extract and segment a moving object. However, it is difficult to extract the object when the gray level of the background is varied due to illumination condition in the real circumstance. In this paper we propose the segmentation algorithm to extract effectively the object in spite of the illumination change. In order to minimize the effect of illumination, the proposed algorithm is composed of three modes according to the background generation and the illuminational change. Then the object is finally obtained by using projection and the morphological operator in post-processing. A good segmentation performance is demonstrated by the simulation result.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.37-45
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• 2013

Objective: This study describes the change of operator performance in drastic change of illumination level, and proposes an alternative method to cope with it. Background: The control standard of illumination for nuclear power plants(NPPs) is based on the set of limit criteria for maintaining a specific illumination level. However, there is a possibility to cause human errors according to the psychological and physiological influences to operators in the situation of drastic change of illumination such as SBO(Station Black Out), so a basic study is necessary to review the current approach. Method: We assessed the visual fatigue, subjective work load and task performance according to the three illumination situations(Normal Illumination, Emergency Illumination, and Drastic Change of Illumination). Result: Research finding shows that there are not significant differences in task performance between normal illumination (1,000lx level) and emergency illumination (100lx level), only if beyond the dark adaptation limit. However, subjective work load on mental demand and visual fatigue show a potential challenge to visual performance in drastic change of illumination. Conclusion/Application: Several trials can complement this challenge in NPPs by applying 3-way communication, enhancing readability of procedures, and managing the visual factors affecting the operators' performance through a Visual Environment Management Program including visual health aspects, etc.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.35-43
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• 2002

The spectral color resolution of an image is very important in color image analysis. Two factors influencing the spectral color resolution of an image are illumination intensity and lens aperture for a selected vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined in the study. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. The role of illumination intensity in machine vision was also described and a computer program for simulating the optimal combination of two factors was implemented for verifying the related algorithm. It was possible to estimate the non-saturating range of the illumination intensity (input voltage in the study) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.42.1-42
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• 2001

This paper presents a fuzzy-based method for classification skin color object in a complex background under varying illumination. Parameters of fuzzy rule base are generated using a genetic algorithm(GA). The color model is used in the YCbCr color space. We propose a unique fuzzy system in order to accommodate varying background color and illumination condition. This fuzzy system approach to skin color classification is discussed along with an overview of YCbCr color space.