• Journal of the Korea Computer Graphics Society
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• v.29 no.5
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• pp.31-40
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• 2023

As display resolution increases, many apps also tend to include high-resolution texture maps. Recent advancements in deep-learning-based image super-resolution techniques make it possible to automate high-resolution texture generation. However, there is still a lack of comprehensive analysis of the application of these techniques to texture maps. In this paper, we selected three recent super-resolution techniques, namely BSRGAN, Real-ESRGAN, and SwinIR (classical and real-world image SR), and applied them to upscale texture maps. We then conducted a quantitative and qualitative analysis of the experimental results. The findings revealed various artifacts after upscaling, which indicates that there are still limitations in directly applying super-resolution techniques to texture-map upscaling.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.162-169
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• 2019

Non-destructive freshness measurement using spectroscopy has been carried out several times, but research on freshness and freshness has not been conducted. Therefore the purpose of this study is to develop a system for visually measuring and quantifying the air sack inside the egg by non - destructive method. The experimental environment which designed a small chamber was composed of 850nm band of two IR lasers, IR camera and two servo motors to acquire air sack Images. When the air sack volume ratio is 2.9% or less and the density is 0.9800 or more, the Haugh Unit value is 60 or more It was judged to be a fresh egg of a grade B or higher. These results mean, using the weight measurement, nondestructive decision system, and freshness evaluating algorithm. It can be expected to distinguish grade B or more marketable eggs without using destructive methods.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.180-191
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• 2016

When up-scaling algorithms for visible light images are applied to infrared (IR) images, they rarely work because IR images are usually blurred. In order to solve such a problem, this paper proposes an up-scaling algorithm for IR images. We employ adaptive dynamic range encoding (ADRC) as a simple classifier based on the observation that IR images have weak details. Also, since human visual systems are more sensitive to edges, our algorithm focuses on edges. Then, we add pre-processing in learning phase. As a result, we can improve visibility of IR images without increasing computational cost. Comparing with Anchored neighborhood regression (A+), the proposed algorithm provides better results. In terms of just noticeable blur, the proposed algorithm shows higher values by 0.0201 than the A+, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.494-504
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• 2004

The researches about gaze detection have been much developed with many applications. Most previous researches only rely on image processing algorithm, so they take much processing time and have many constraints. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.2 cm of RMS error.

• International Journal of Contents
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• v.2 no.3
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• pp.22-26
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• 2006

In this paper we introduce a new circle detection algorithm for occluded on/off pupil and iris boundary extraction. The proposed algorithm employs 7-step processing to detect a center and radius of occluded on/off eye images using the property of the chords. The algorithm deals with two types of occluded pupil and iris boundary information; one is composed of circle-shaped, incomplete objects, which is called occluded on iris images and the other type consists of arc objects in which circular information has partially disappeared, called occluded off iris images. This method shows that the center and radius of iris boundary can be detected from as little as one-third of the occluded on/off iris information image. It is also shown that the proposed algorithm computed the center and radius of the incomplete iris boundary information which has partially occluded and disappeared. Experimental results on RGB images and IR images show that the proposed method has encouraging performance of boundary detection for pupil and iris segmentation. The experimental results show satisfactorily the detection of circle from incomplete circle shape information which is occluded as well as the detection of pupil/iris boundary circle of the occluded on/off image.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.1-8
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• 2010

The researches about gaze recognition which current user gazes and finds the location have increasingly developed to have many application. The gaze recognition of existence all about researches have got problems because of using equipment that Infrared(IR) LED, IR camera and head-mounted of high price. This study propose and implement the gaze recognition system based on SVM using a single PC Web camera. The proposed system that divide the gaze location of 36 per 9 and 4 to recognize gaze location of 4 direction and 9 direction recognize user's gaze. Also, the proposed system had apply on image filtering method using difference image entropy to improve performance of gaze recognition. The propose system was implements experiments on the comparison of proposed difference image entropy gaze recognition system, gaze recognition system using eye corner and eye's center and gaze recognition system based on PCA to evaluate performance of proposed system. The experimental results, recognition rate of 4 direction was 94.42% and 9 direction was 81.33% for the gaze recognition system based on proposed SVM. 4 direction was 95.37% and 9 direction was 82.25%, when image filtering method using difference image entropy implemented. The experimental results proved the high performance better than existed gaze recognition system.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1470-1473
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• 2015

최근 빠른 인터넷 속도를 이용하여 SNS (Social Network Service), 인터넷 방송 등의 엔터테인먼트를 즐기는 사용자가 증가하였다. 이와 함께 직접 사진, 동영상 등의 멀티미디어를 직접 제작해 제공하는 사례도 크게 증가함에 따라 영상처리 기술이 발전하였다. 이에 따라 셀프촬영이 점점 증가하고 있지만, 동영상의 경우는 셀프촬영을 하는데 있어 한계가 있다. 이 문제를 해결하기 위한 한 방법으로 영상처리를 이용할 수 있다. 하지만 현재의 기술은 고성능에 초점이 맞춰있기 때문에 시스템 구현을 위해 비용 낭비가 발생할 수 있다. 따라서 본 논문에서는 셀프 동영상 촬영 분야의 적외선 영상처리 기반 저비용 사용자 추적 시스템을 제안한다. 실제 단순히 인식률을 측정한 결과 80%를 보였으며, 속도에 따라 1.5m/s에서 76%의 인식률을 보였다.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.147-155
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• 2013

The nominal radiometric calibration equation and additional five algorithms are applied in the infrared channel radiometric calibration for the COMS (Communication, Ocean, Meteorological Satellite) MI (Meteorological Imager). The processing end time of the radiometric calibration is directly related with the start time of geometric calibration processing since the geometric calibration processing is followed by that of the radiometric calibration. This paper describes comparison and analysis results for geometric calibration processing using two types of the radiometric calibration results, outputs from only the nominal radiometric calibration equation and outputs from the complete one (the nominal radiometric calibration equation with additional five algorithms), to propose a method with the earlier start time of the geometric calibration processing. Experimental results show that both of radiometric calibration results, from the nominal radiometric calibration equation with a fast processing speed and from the complete one with accurate radiometric values, can be used in the geometric calibration as the appropriate inputs because those processing results satisfied the requirements of geometric calibration processing accuracy. Thus the radiometric calibration results from the nominal radiometric calibration equation can be used to improve geometric calibration processing time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2156-2170
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• 2020

This paper presents a fire detection algorithm with a minimal false detection rate, intended for a thermal imaging surveillance environment, whose properties vary depending on temporal conditions of day or night and environmental changes. This algorithm was designed to minimize the false detection alarm rate while ensuring a high detection rate, as required in fire detection applications. It was necessary to reduce false fire detections due to non-flame elements occurring when existing fixed threshold-based fire detection methods were applied. To this end, adaptive flame thresholds that varied depending on the characteristics of input images, as well as the center of gravity of the heat-source and hot-source regions, were analyzed in an attempt to minimize such non-flame elements in the phase of selecting flame candidate blocks. Also, to remove any false detection elements caused by camera shaking, one of the most frequently raised issues at outdoor sites, preliminary decision thresholds were adaptively set to the motion pixel ratio of input images to maximize the accuracy of the preliminary decision. Finally, in addition to the preliminary decision results, the texture correlation and intensity of the flame candidate blocks were averaged for a specific period of time and tested for their conformity with the fire decision conditions before making the final decision. To verify the fire detection performance of the proposed algorithm, a total of ten test videos were subjected to computer simulation. As a result, the fire detection accuracy of the proposed algorithm was determined to be 94.24%, with minimum false detection, demonstrating its improved performance and practicality compared to previous fixed threshold-based algorithms.