• Archives of design research
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• v.16 no.3
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• pp.329-340
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• 2003

The purpose of this study is to provide the methods of harmony in color combination of environmental color for apartment in order to improve the image of the urban landscape. For this study, apartment in Iksan City was selected is a sample and twenty two apartments were analyzed. This framework of this study is A. Hard and L. Sivik's color combination model based on Natural Color System. This study examines various theories on environmental color perception and new approaches to color aesthetics, and tries to present perceptual properties that can be applied to environmental color design First, the principle of color harmony feeling in based on nuance and tone. Therefore, to control brightness and chromaticness with are related with nuance is important in color combination. Second, the aesthetic experience in color preception can be defined as a combined effect of similarities and differences of color attributes. Third, color harmony theory is one of the areas that can be benefit a great deal from and interdisciplinary approach, add empirical study such as this can be used as a basis for environmental color design and evaluation.

• Journal of Korean Ophthalmic Optics Society
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• v.5 no.1
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• pp.31-37
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• 2000

In order to color analyze of in Farnsworth Test Panel D-15 using a Protan, Deutan and Tritan test, we introduced the CIE system so that measured the reflectance light spectrum intensity in the 380~780 nm wavelength regions. The color difference of Panel D-15 was depended on the intensity of reflectance ratio in the 400~450 nm, 500~600 nm and more than 650 nm wavelength regions. From the reflectance spectra, we obtained the tristimulus X, Y, Z values, the $L^*a^*b^*$ and $L^*ab$ values of the 3-Dimension CIELAB system in a complement plane and light-darkness axis, the $U^*V^*$ values and the x, y values of chromaticity coordinates.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.561-565
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• 2011

This paper presents an imaging system for reconstruction of enhanced color images using the conventional Bayer CFA. By extracting various colors such as RGBCY from two sequential images which consist of a image by broadband G channel lens filter and the other image captured without one, the proposed color image reconstruction system can reduce the computational complexity for demosaicking and make high resolution color information without aliasing artifacts. Because the proposed system uses the common Bayer CFA image sensor, fabricating a new type of CFA is not necessary for obtaining a multi-spectral image, which can be easily extensible for applications of multi-spectral imaging. Finally, in order to verify the performance of the proposed system, experimental results are performed. By comparing with the existing demosaicking methods, the proposed camera system showed the significant improvements in the sense of color resolution.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.47-55
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• 2000

In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.113-121
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• 2009

In order to retrieve images with different emotions in regions of the images, this paper proposes the image retrieval system using emotion sketch. The proposed retrieval system divides an image into $17{\times}17$ sub-regions and extracts emotion features in each sub-region. In order to extract the emotion features, this paper uses emotion colors on 160 emotion words from H. Nagumo's color scheme imaging chart. We calculate a histogram of each sub-region and consider one emotion word having the maximal value as a representative emotion word of the sub-region. The system demonstrates the effectiveness of the proposed emotion sketch and our experimental results show that the system successfully retrieves on the Corel image database.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.74-79
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• 2017

The Geostationary Ocean Color Imager (GOCI), the world's first ocean color sensor operated in a geostationary orbit, can be utilized to mitigate damages by monitoring marine disasters in real time such as red tides, green algae, sargassum, cold pools, typhoons, and so on. In this paper, we described a methodology and procedure for processing GOCI data in order to maximize its utilization potential. The GOCI data processing procedure is divided into data reception, data processing, and data distribution. The kinds of GOCI data are classified as raw, level 1, and level 2. "Raw" refers to an unstructured data type immediately generated after reception by satellite communications. Level 1 is defined as a radiance data type of two dimensions, generated after radiometric and geometric corrections for raw data. Level 2 indicates an ocean color data type from level-1 data using ocean color algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.1-13
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• 2011

The aim of this study is to analyze the emotion adjectives for light emitting diode(LED) light colors using a twofold adjective image scales from Kobayashi and I.R.I. A set of psychophysical experiments using category judgment was conducted in an LED light color simulation system, in order to evaluate each emotion scale coordinate for those test light colors in both adjective image scales. In total, 49 test light colors from a combination of 6 color series were assessed by 15 human observers. As a result, Kobayashi adjective image scale clearly expressed to emotion adjectives of 'Dynamic', 'Casual', 'Chic', 'Cool-casual', 'Modern', and 'Natural' for different hues. In contrast, I.R.I adjective image scale expressed only 2 adjectives of 'dynamic' and 'luxurious' for the all hues.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.300-306
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• 2012

An image attention model and its application to image quality assessment are discussed in this paper. The attention model is based on rarity quantification, which is related to self-information to attract the attention in an image. It is relatively simpler than the others but results in taking more consideration of global contrasts between a pixel and the whole image. The visual attention model is used to develop a local distortion predictor, named color visual differences predictor (CVDP), in color images in order to effectively detect luminance and color distortions.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.353-362
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• 1993

The purpose of this study is to develop a crop-row detector which can be applied to an automatic row following control for cultivators or thinning machines. In this report, a possibility of new crop-row detecting method was discussed. This detecting method consists of two principal means. One is the hardware means to convert the two dimensional crop-row vision to the compacted one dimensional information. The conversion is achieved by a color line sensor and a rotating mirror. In order to extract crop-row , R and G signals of RGB color system are used. The locations of two different points on the target row are detected by this means. Another is the software means to estimate the offset value and the heading angle between the detector and the target row which can be assumed as a straight line. As a result of discussion, it was concluded that this detecting method would be accurate enough for practical use.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.176-190
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• 2002

According as vehicles increases, system such as Advanced Drivers Assistance System(ADAS ) to inform forward situation to driver is required. In this paper, we proposes method to detect forward vehicles and lane from sequential color images by basis process to inform forward situation to driver. We detect a front vehicle using that shadow area exists on part under vehicles and that road area occupies many parts even if road traffic is confused. We detect lane information using that lane part is white order by reverse characteristic of shadow area. This method shows good result in case road is confused or there is direction indication to road. HSV color space is selected for color modeling. This method uses saturation component and value component in HSV color model to detect vehicles and lane. It uses statistics features of HSV component and position to know whether detected vehicles area is vehicles such as vehicles previous frame. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and Present the results such as processing time, accuracy and vehicles detection against the images.