• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.24-27
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• 2009

Architectural lighting is an important factor to inform brand image to public for a headquarter building at night The government encourages to clients to apply architectural lighting to their buildings for the nightscape. In these days, variable lightings and lighting designs are applied to a building in the world. Therefore, the purpose of this study is to analyze and compare architectural lighting design on the various office buildings in Hongkong, Shanghai and Seoul with measured luminance and photographic images at night-time.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1909-1918
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• 2016

This paper presents a unified framework for joint Convolutional Neural Network (CNN) based vehicle detection by leveraging multi-spectral image pairs. With the observation that under challenging environments such as night vision and limited light source, vehicle detection in a single color image can be more tractable by using additional far-infrared (FIR) image, we design joint CNN architecture for both RGB and FIR image pairs. We assume that a score map from joint CNN applied to overall image can be considered as confidence of vehicle existence. To deal with various scale ratios of vehicle candidates, multi-scale images are first generated scaling an image according to possible scale ratio of vehicles. The vehicle candidates are then detected on local maximal on each score maps. The generation of overlapped candidates is prevented with non-maximal suppression on multi-scale score maps. The experimental results show that our framework have superior performance than conventional methods with a joint framework of multi-spectral image pairs reducing false positive generated by conventional vehicle detection framework using only single color image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.43-49
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• 2021

A small infrared image homing system is a tracking system that has an infrared image sensor that identifies a target through the day and night infrared image processing of the target on the ground and searches for and detects the target with respect to the main target. This paper describes the development of a board equipped with a high-speed CPU and FPGA (Field Programmable Gate Array) to identify target through real-time image processing by acquiring target information through infrared image. We propose a CPU-FPGA combining architecture for CPU and FPGA selection and video signal processing, and also describe a controller design using FPGA to control infrared sensor.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.163-172
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• 2012

A driver assistance system is critical to improve a convenience and stability of vehicle driving. Several systems have been already commercialized such as adaptive cruise control system and forward collision warning system. Efficient vehicle detection is very important to improve such driver assistance systems. Most existing vehicle detection systems are based on a radar system, which measures distance between a host and leading (or oncoming) vehicles under various weather conditions. However, it requires high deployment cost and complexity overload when there are many vehicles. A camera based vehicle detection technique is also good alternative method because of low cost and simple implementation. In general, night time vehicle detection is more complicated than day time vehicle detection, because it is much more difficult to distinguish the vehicle's features such as outline and color under the dim environment. This paper proposes a method to detect vehicles at night time using analysis of a captured color space with reduction of reflection and other light sources in images. Four colors spaces, namely RGB, YCbCr, normalized RGB and Ruta-RGB, are compared each other and evaluated. A suboptimal threshold value is determined by Otsu algorithm and applied to extract candidates of taillights of leading vehicles. Statistical features such as mean, variance, skewness, kurtosis, and entropy are extracted from the candidate regions and used as feature vector for SVM(Support Vector Machine) classifier. According to our simulation results, the proposed statistical feature based SVM provides relatively high performances of leading vehicle detection with various distances in variable nighttime environments.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.27-35
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• 2009

This study aimed to find problems of nightscape of Anyang-si through examination of behavioral pattern at night and measurement of illumination and luminance in accordance with regional classification following 6 regional classifications on the basis of ur1xm characteristic of Anyang-si. Basic concept of nightscape creation was application of improvement plan with analysis of regional problems and creation of artistic value to enhance image of Anyang-si as a city of art. To obtain balance and unity of night illumination, concept of light zoning was applied to smooth-transform method by regions. Especially, right to view harmonized with surrounding scenery was secured through creating gradual skyline compatible with neighbor buildings using division of each buildings according to their heights. In addition, way to improvement of night lighting environment was proposed as to illumination, height, type of lamp and arrangement of street lights and furniture in accordance with regional characteristics.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.201-212
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• 2011

In this paper, we suggest a system of detecting a vehicle with lane violation, which can detect the vehicle with lane violation, by using the feature point tracking. The whole algorism in the suggested system of detecting a vehicle with lane violation is composed of three stages such as feature extraction, register and tracking in feature for the tracking-targeted vehicle, and detecting a vehicle with lane violation. The feature is extracted from the morphological gradient image, which results in constructing robust detection system against shadows, weather conditions, head lights and illumination conditions without distinction day and night. The system shows excellent performance for the data captured at day time, night time, and rainy night time as much as 99.49% for positive recognition ratio and 0.51% for error ratio. Also the system is so fast as much as 91.34 frames per second in average that it may be possible for real-time processing.

• Journal of Korean Theatre Studies Association
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• no.48
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• pp.359-384
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• 2012

The purpose of this study was to explore the theatrical aesthetics of the performances which was produced by the theater director, Yang Jung-Ung. Yang has been one of the most influential directors working in Korea in the last 15 years. He has put up performances all over the world with the theater members from his company called Yohangza, which was founded by him in 1997, and working as the director, portrayed his style of the theatrical aesthetics through the works of its plays and musical products. In 2012, this company performed A Midsummer Night's Dream at Shakespeare's Globe Theatre. A Midsummer Night's Dream was invited to be staged at the Barbican Center in 2006. In the same year, it received the grand prize and the Audience Choice award at the Gdansk International Shakespeare Festival in Poland. The musical products like A Good Woman from Seoul and the modern Opera Wozeck are representative works of Yohangza, which are known for a unique way of exploring the meaning of life. The 2009 plays Hamlet and Peer Gynt represent Yohangza's simpler yet more insightful theatrical style. Peer Gynt, which debuted at the LG Art Center, made headlines for its innovative staging. It received the grand prix, Best Director and Best Stage Art awards at the 2009 Korea Theater Awards. Yohangza's plays show two-side "image-based" works. The company drastically reduced verbal lines and enriched the plays with Korean sentiment and aesthetics, but their scripts contained many poetic lines full of overtones. They showed a theatrical mise-en-scene of images, energetic dance, songs in chorus and percussion. For example, Korean sentiments were subtly blended into the two Shakespeare's plays, A Midsummer Night's Dream and Twelfth Nights. Their performance combines music, mime, song and dance to create an exhilarating adaptation of Shakespeare's inventive and glittering comedy. In addition, the style of Yohangza Theatre Company is a collision of the past and the present: a reworking of existing Korean styles and themes infused with contemporary elements and full of unique exploration in the plays.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.517-528
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• 2007

Extraction of the coastal boundary is important because the boundary serves as a reference in the demarcation of maritime zones such as territorial sea, contiguous zone, and exclusive economic zone. Accurate nautical charts also depend on well established, accurate, consistent, and current coastline delineation. However, to identify the precise location of the coastal boundary is a difficult task due to tidal and wave motions. This paper presents an efficient way to extract coastlines by applying digital image processing techniques to Synthetic Aperture Radar (SAR) imagery. Over the past few years, satellite-based SAR and high resolution airborne SAR images have become available, and SAR has been evaluated as a new mapping technology. Using remotely sensed data gives benefits in several aspects, especially SAR is largely unaffected by weather constraints, is operational at night time over a large area, and provides high contrast between water and land areas. Various image processing techniques including region growing, texture-based image segmentation, local entropy method, and refinement with image pyramid were implemented to extract the coastline in this study. Finally, the results were compared with existing coastline data derived from aerial photographs.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.467-472
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• 2005

The principal objective of enhancement methods is to process an image so that the output image is more suitable than the original image lot a specific application. Images taken in the night can be low-contrast images because of poor environments. In this paper, we compared the performance of Image Contrast Enhancement Technique Using Clustering Algorithm(ICECA) with those of color adjustment methods such as Histogram Equalization(HE), Brightness Preserving Bi-Histogram Equalization(BBHE), and the Multi-Scale Refiner(MSR). We compared these methods by applying the image enhancement methods to a set of diverse images.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.516-521
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• 2010

In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.