• Journal of Korea Game Society
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• v.16 no.1
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• pp.111-118
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• 2016

This paper proposes the mathematical model of Fresnel effect used to illuminate and simulate a surface character model for defense game play. The term illumination is used to represent the process by which the amount of light reaching a surface character model used on game play is determined. The character surface shaders generally use a mathematical model to predict how light will reflect on triangles. The shading normally represents the methods used to determine the color and intensity of light reflected toward the viewer for each pixel representing the character surface model of the game. This model computes the reflection and transmission coefficients and compares simulated results to the Fresnel equations for the real game improvement.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.71-79
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• 2011

The objective of the imaging pipeline is to transform the original scene into a display image that appear similar, Generally, gamma adjustment or histogram-based method is modified to improve the contrast and detail. However, this is insufficient as the intensity and the chromaticity of illumination vary with geometric position. Thus, MSR (Multi-Scale Retinex) has been proposed. the MSR is based on a channel-independent logarithm, and it is dependent on the scale of the Gaussian filter, which varies according to input image. Therefore, after correcting the color, image quality degradations, such as halo, graying-out, and dominated color, may occur. Accordingly, this paper presents a novel color correction method using a modified image formation model in which the image is divided into three components such as global illumination, local illumination, and reflectance. The global illumination is obtained through Gaussian filtering of the original image, and the local illumination is estimated by using JND-based adaptive filter. Thereafter, the reflectance is estimated by dividing the original image by the estimated global and the local illumination to remove the influence of the illumination effects. The output image is obtained based on sRGB color representation. The experiment results show that the proposed method yields better performance of color correction over the conventional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.771-788
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• 2020

Detection of abandoned objects for smart video surveillance should be robust and accurate in various situations with low computational costs. This paper presents a new algorithm for abandoned object detection based on the dual background model. Through the template registration of a candidate stationary object and presence authentication methods presented in this paper, we can handle some complex cases such as occlusions, illumination changes, long-term abandonment, and owner's re-attendance as well as general detection of abandoned objects. The proposed algorithm also analyzes video frames at specific intervals rather than consecutive video frames to reduce the computational overhead. For performance evaluation, we experimented with the algorithm using the well-known PETS2006, ABODA datasets, and our video dataset in a live streaming environment, which shows that the proposed algorithm works well in various situations.

• Smart Media Journal
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• v.13 no.2
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• pp.85-94
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• 2024

Artificial Intelligence of Things (AIoT), which combines AI and the Internet of Things (IoT), has recently gained popularity. Deep neural networks (DNNs) have achieved great success in many applications. Deploying complex AI models on embedded boards, nevertheless, may be challenging due to computational limitations or intelligent model complexity. This paper focuses on an AIoT-based system for smart sewing automation using edge devices. Our technique included developing a detection model and a decision tree for a sufficient testing scenario. YOLOv5 set the stage for our defective sewing stitches detection model, to detect anomalies and classify the sewing patterns. According to the experimental testing, the proposed approach achieved a perfect score with accuracy and F1score of 1.0, False Positive Rate (FPR), False Negative Rate (FNR) of 0, and a speed of 0.07 seconds with file size 2.43MB.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.955-956
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• 2008

This paper presents a new method for illumination normalization in eye detection. Based on the retinex image formation model, we employ the discrete wavelet transform to remove the lighting effect in face image data. The final result based on the proposed method shows the better performance in detecting eyes compared with previous work.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.711-720
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• 2012

In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.960-967
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• 2013

Shape recognition of solder ball bumps in a BGA (Ball Grid Array) is an important issue in flip chip bonding technology. In particular, the semiconductor industry has required faster and more accurate inspection of micron-size solder bumps in flip chip bonding as the density of balls has increased dramatically. The difficulty of this issue comes from specular reflection on the metal ball. Shape recognition of a metal ball is a very realproblem for computer vision systems. Specular reflection of the metal ball appears, disappears, or changes its image abruptly due to tiny movementson behalf of the viewer. This paper presents a practical shape recognition method for three dimensional (3-D) inspection of a BGA using a 5-step ring illumination device. When the ring light illuminates the balls, distinctive specularity images of the balls, which are referred to as "iso-slope contours" in this paper, are shown. By using a mathematical reflectance model, we can drive the 3-D shape information of the ball in aquantitative manner. The experimental results show the usefulness of the method for industrial application in terms of time and accuracy.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.268-269
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• 2008

Moving object detection is a fundamental technique in visual surveillance. Robust technique to enhance performance of moving object detection is required for several bad conditions in real external circumtance. In case of sudden illumination change in outdoor condition, many objects are determined as moving object though they are not really moving, but just their illumination changes. This makes the detection result untrustworthy. In this paper, robust moving object detection to sudden illumination change using gaussian mixture background model and new texture information using background from the weighted sum of recent images is proposed.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.663-671
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• 2014

LED lamp arrangement is a critical issue in indoor visible light communication (VLC) system. In this paper, we analyze the illumination distribution under the arrangement of $2{\times}3$ and propose a method to find the optimal lamp arrangement. The method, based on the MIMO (Multiple Input/Multiple Output) system model and taking the first order reflection into consideration, enables accurate analysis of the arrangement of the LED lamps for any room. The studies show that under the optimal arrangement the uniformity of illumination is improved from 0.55 to 0.86, which guarantees that users can get almost equal lighting effects, no matter where they locate themselves. At the same time, the RMS delay spread distribution which is used to evaluate the inter-signal-interference (ISI) is analyzed, and the simulation results indicate that the optimal arrangement also can improve the communication quality by reducing the fluctuation of the RMS delay spread.