• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1388-1391
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• 2010

In this paper, we present a design and implementation of U-learning system using pen based augmented reality approach. Student has been given a smart pen and a smart study book, which is similar to the printed material already serviced. However, we print the study book using CMY inks, and embed perceptually invisible dot patterns using K ink. Smart pen includes (1) IR LED for illumination, IR pass filter for extracting the dot patterns, and (3) camera for image captures. From the image sequences, we perform topology analysis which determines the topological distance between dot pixels, and perform error correction decoding using four position symbols and five CRC symbols. When a student touches a smart study books with our smart pen, we show him/her multimedia (visual/audio) information which is exactly related with the selected region. Our scheme can embed 16 bit information, which is more than 200% larger than previous scheme, which supports 7 bits or 8 bits information.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.96-110
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• 2017

Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.45-59
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• 2006

In this study, the effects of the surface topographical characteristics on the meteorological fields are examined in a mesoscale meteorlolgical model. We calculated the direct solar radiation using the illumination angle considering the inclination of topography and tried to find out its effect on meteorological fields. In above experiments, we selected two cases for the clear day and the cloudy day to show the effect of weather and represented the results for two cases. In the correction of the direct solar radiation, the results of two cases indicate that there are obvious differences on the steep Taeback and Soback mountains. And on the time-series analysis the east-facing slope of these mountains receives the more direct solar radiation about $10-60W/m^2$ in the morning hours but lesser in the afternoon hours than the horizontal surface while it is opposite on the west-facing slope. And the results mentioned above are more obvious at clear day. With the same analysis method, at clear day, the surface skin temperature is higher at all hours than that on horizontal surface on the both of slope. At cloudy and rainy day, the surface skin temperature on the east-facing slope is higher in the morning hours but lower in the afternoon hours than that on horizontal surface. But on the west-facing slope, it is higher at all hours than that on horizontal surface. In the two cases, the temperature considering the slope of surface is almost higher than that on the horizontal surface. The wind is stronger than that on the horizontal surface with increasing pressure gradient force according as increasing temperature gradient around the Taeback and the Soback mountains.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.535-546
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• 2010

Digital images have undesired color casts due to various illumination conditions and intrinsic characteristics of cameras. Since the color casts in the images deteriorate performance of color representations, color correction is required for further analysis of images. In this paper, an algorithm for detection and removal of color casts is presented. The proposed algorithm consists of four steps: retrieving similar image using color by correlation, extraction of near neutral color regions, kernel density estimation, and removal of color casts. Ambiguities in near neutral color regions are excluded based on kernel density estimation by the color by correlation algorithm. The method determines whether there are color casts by chromaticity distributions in near neutral color regions, and removes color casts for color constancy. Experimental results suggest that the proposed method outperforms the gray world algorithm and the color by correlation algorithm.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.13-21
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• 2009

This paper describes research of image enhancement for detection of face area. Typical face recognition algorithms used fixed parameter filtering algorithms to optimize face images for the recognition process. A fixed filtering scheme introduces errors when applied to face images captured in various different environmental conditions. For acquiring face image of good quality from the image including complex background and illumination, we propose a method for image enhancement using the categories based on the image intensity values. When an image is acquired average values of image from sub-window are computed and then compared to training values that were computed during preprocessing. The category is selected and the most suitable image filter method is applied to the image. We used histogram equalization, and gamma correction filters with two different parameters, and then used the most suitable filter among those three. An increase in enrollment of filtered images was observed compared to enrollment rates of the original images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.35-43
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• 2007

With the current trend of digital convergence in mobile phone, imaging devices such as cameras, displays and beam-projectors have been made smaller and become into mobile phones. Especially, built-in beam-projectors (we call it mobile beam-projector hereafter) have been developed to overcome small screen size of mobile display and to provide the realistic image while watching movies or broadcasting. However, mobile beam-projector can project an original image on various colored-screen, different from general data projector with white screen, thereby degrading the image quality of projected images. Therefore, this paper proposed a method of correcting projected images on colored-screens by adapting color constancy theory that has been mainly used for illumination estimation.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.61-68
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• 2016

Surveillance cameras have been installed in many places because security and safety has become an important issue in modern society. However, watching surveillance videos and judging accidental situations is very labor-intensive and time-consuming. So now, requests for research to automatically analyze the surveillance videos is growing. In this paper, we propose a surveillance system to track multiple persons in videos and to summarize the videos based on tracking information. The proposed surveillance summarization system applies an adaptive illumination correction, subtracts the background, detects multiple persons, tracks the persons, and saves their tracking information in a database. The tracking information includes tracking one's path, their movement status, length of staying time at the location, enterance/exit times, and so on. The movement status is classified into six statuses(Enter, Stay, Slow, Normal, Fast, and Exit). This proposed summarization system provides a person's status as a graph in time and space and helps to quickly determine the status of the tracked person.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.1-7
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• 1998

SAR data can be achieved independently of weather conditions or sun illumination which is main limitation of electro-optical sensor to get image. The information from imagery can be more enlarged using Shh data be-cause SAR data offers different information from electro-optical sensor. SAR data contains various distortions caused by the radar specification and geometric properties of data acquisition. These distortions should be removed to get the information with acceptable accuracy. In this study, we aimed to correct the radiometric distortion in Shh image caused by the geometric property of the object. For this purpose, we simulated the SAR image by modelling of the power of return beam which is variable according to the geometric configuration between SAR antenna and ground object. Dividing the SAR image by the simulation image, then, we can get the radiometrically corrected image. As a result of this study, we could minimize the effect of radiometric distortion in achieving some qualitative information from SAR image for the related field, such as Geospatial Information System.

• Journal of Biosystems Engineering
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• v.37 no.6
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• pp.404-410
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• 2012

Purpose: The objective of this research was to select high quality cucumber (cucumis sativus) seed by classifying into viable or non-viable one using Raman spectroscopy. Method: Both transmission and back-scattering Raman spectra of viable and non-viable seeds in the range from $150cm^{-1}$ to $1890cm^{-1}$ were collected with a laser illumination. Results: The Raman spectra of cucumber seed showed Raman peaks with features of polyunsaturated fatty acids. The partial least squares-discriminant analysis (PLS-DA) to predict viable seeds was developed with measured transmission and backscattering spectra with Raman spectroscopy and germination test results. Various types of spectra pretreatment were investigated to develop the classification models. The results of developed PLS-DA models using the transmission spectra with mean normalization or range normalization, and back-scattering spectra with mean normalization treatment or baseline correction showed 100% discrimination accuracy. Conclusions: These results showed that Raman spectroscopy technologies can be used to select the high quality cucumber seeds.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.159-175
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• 2015

The two-dimensional QR code has advantages such as directional nature, enough data storage capacity, ability of error correction, and ability of data restoration. There are two major issues like speed and correctiveness of recognition in the two-dimensional QR code. Therefore, this paper proposes a morphology-based algorithm of detecting the interest region of a barcode. Our research contents can be summarized as follows. First, the interest region of a barcode image was detected by close operations in morphology. Second, after that, the boundary of the barcode are detected by intersecting four cross line outside in a code. Three, the projected image is then rectified into a two-dimensional barcode in a square shape by the reverse-perspective transform. In result, it shows that our detection and recognition rates for the barcode image is also 97.20% and 94.80%, respectively and that outperforms than previous methods in various illumination and distorted image environments.