• Korean Journal of Artificial Intelligence
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• v.12 no.3
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• pp.1-7
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• 2024

In this paper, we propose an innovative super-resolution technique to address the issue of reduced accuracy in license plate recognition caused by low-resolution images. Conventional vehicle license plate recognition systems have relied on images obtained from fixed surveillance cameras for traffic detection to perform vehicle detection, tracking, and license plate recognition. However, during this process, image quality degradation occurred due to the physical distance between the camera and the vehicle, vehicle movement, and external environmental factors such as weather and lighting conditions. In particular, the acquisition of low-resolution images due to camera performance limitations has been a major cause of significantly reduced accuracy in license plate recognition. To solve this problem, we propose a Single Image Super-Resolution (SISR) model with a parallel structure that combines Multi-Scale and Attention Mechanism. This model is capable of effectively extracting features at various scales and focusing on important areas. Specifically, it generates feature maps of various sizes through a multi-branch structure and emphasizes the key features of license plates using an Attention Mechanism. Experimental results show that the proposed model demonstrates significantly improved recognition accuracy compared to existing vehicle license plate super-resolution methods using Bicubic Interpolation.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.70-78
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• 2007

The performance of face recognition is greatly affected by the illumination effect because intra-person variation under different lighting conditions can be much bigger than the inter-person variation. In this paper, we propose an illumination robust face recognition by separating identity factor and illumination factor using the symmetric bilinear models. The translation procedure in the bilinear model requires a repetitive computation of matrix inverse operation to reach the identity and illumination factors. Sometimes, this computation may result in a nonconvergent case when the observation has an noisy information. To alleviate this situation, we suggest a ridge regressive bilinear model that combines the ridge regression into the bilinear model. This combination provides some advantages: it makes the bilinear model more stable by shrinking the range of identity and illumination factors appropriately, and it improves the recognition performance by reducing the insignificant factors effectively. Experiment results show that the ridge regressive bilinear model outperforms significantly other existing methods such as the eigenface, quotient image, and the bilinear model in terms of the recognition rate under a variety of illuminations.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.89-99
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• 2016

One of the fundamental elements in developing mixed reality applications is to effectively analyze and apply the environmental lighting information to image synthesis. In particular, interactive applications require to process dynamically varying lighting sources in real-time, reflecting them properly in rendering results. Previous related works are not often appropriate for this because they are usually designed to synthesize photorealistic images, generating too many, often exponentially increasing, light sources or having too heavy a computational complexity. In this paper, we present a fast light source estimation technique that aims to search for primary light sources on the fly from a sequence of video images taken by a camera equipped with a fisheye lens. In contrast to previous methods, our technique can adust the number of found light sources approximately to the size that a user specifies. Thus, it can be effectively used in Phong-illumination-model-based direct illumination or soft shadow generation through light sampling over area lights.

• Journal of the Korea Computer Graphics Society
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• v.17 no.4
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• pp.31-40
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• 2011

Projector-based visual systems are widely used for VR and experience display applications. But the illumination irregularity on the screen surface due to the screen material and its light reflection properties sometimes deteriorates the user experience. This phenomenon is particularly troublesome when the participants of the head tracking VR system such as CAVE or the motion generation experience system continually move around the system. One of reason to illumination irregularity is projector-screen specular reflection component to participant's eye's position and it's analysis needs high computation complexity. Similar to calculate specular lighting term using GPU's programmable shader, Our research adjusts every pixel's brightness in runtime with given 3D screen space model to reduce illumination irregularity. For doing that, Angle-based brightness compensate function are considered for specific screen installation and modified it for GPU-friendly compute and access. Two aspects are implemented, One is function access transformation from angular form to product and the other is piecewise linear interpolate approximation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.43-51
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• 2010

In this paper, we studied line coding technology tendency for high speed data communication at LED-ID (Identification) communication system in indoor environment. A LED-ID technology is a communication using visible ray (RGB) that come out in LED device. It is energy curtailment effect and possible in ubiquitous network service applications. The LED-ID system has the above advantages about that the communication throughout the whole room is enabled by high power lighting and lighting equipment with white colored LED which are easy to install and have good outward appearance. Therefore, the transmission by light waves is more suitable for wireless networks than by radio waves. We compared with the NRZ, AMI, 4B5B, HDB3, 8B10B line coding for efficient in error detection and serves data transmission of high speed.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.1-7
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• 2020

The secure access the lighting, Heating, ventilation, and air conditioning (HVAC), fire safety, and security control boxes of building facilities is the primary objective of future smart buildings. This paper proposes an authorized user access to the electrical, lighting, fire safety, and security control boxes in the smart building, by using color grid coded optical camera communication (OCC) with face recognition Technologies. The existing CCTV subsystem can be used as the face recognition security subsystem for the proposed approach. At the same time a smart device attached camera can used as an OCC receiver of color grid code for user access authentication data sent by the control boxes to proceed authorization. This proposed approach allows increasing an authorization control reliability and highly secured authentication on accessing building facility infrastructure. The result of color grid code sequence received by the unauthorized person and his face identification allows getting good results in security and gaining effectiveness of accessing building facility infrastructure. The proposed concept uses the encoded user access authentication information through control box monitor and the smart device application which detect and decode the color grid coded informations combinations and then send user through the smart building network to building management system for authentication verification in combination with the facial features that gives a high protection level. The proposed concept is implemented on testbed model and experiment results verified for the secured user authentication in real-time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.227-232
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• 2003

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. eased on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.2
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• pp.51-55
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• 1997

The high frequency fluorescnet lighting systems are widely used because of their high luminous efficacy. However, the performance of the fluorescnet lamp at high frequency reveals significant changes depending upon operating frequency, lamp shape, lamp voltage and current while adapting either an electronic or an magnetic ballast. Therefore the matching between the fluorescent lamp and the ballast is the major concern in designing a lighting system. In this paper, high frequency characteristics of the FHF32W lamp is measured in a range of frequencies from 12kHz to 50kHz. And we presented a model of a fluorescnet lamp with non-linear impedance depending on the lamp current. Finally, after identifying the operating condition under negative imped¬ance behavior as lamp current changing, we proposed a method of choosing the optimal parameter of a high frequency fluorescnet lamp and the result is analyzed.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.3-16
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• 2018

Despite the substantial changes made in the product design field to adopt light as an essential design element, there has been little effort to define how customers respond emotionally to the light design of products. Therefore, it is necessary to analyze the emotional effect of light as a new design element. However, previous research focuses solely on deriving optimal lighting conditions to achieve particular emotional effects. Therefore, this paper investigates the customers' desired emotional effects of product's light design. We studied refrigerators that utilize light as the main design element of the product. We applied mixed methods by combining close-ended questions and open-ended question to efficiently derive the desired emotion. Participants were asked to choose the most favorable refrigerator image in each of the twelve image groups and indicate why they choose that image with the short-answer survey form. Approximately one thousand terms were collected, and those terms were classified into 29 groups using thesaurus relationships. The term groups were again classified into the four big emotion categories and labelled as "abstract quality," "light property," "space perception," and "visual comfort." Also, a model of the relationship between desired light style and light properties was proposed, since we observed the light properties related to three other categories. This study used mixed methods to identify the emotional value of a new design element. We suggest that the emotional categories derived and the proposed relationship model could be used to evaluate the product's light design.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.25-36
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• 2008

In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.