• Journal of the Korean Graphic Arts Communication Society
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• v.14 no.2
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• pp.65-80
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• 1996

Ink trap is one of the important factors to determine the color in multi-color overprints. This study was carried out for the purpose for analyzing the relationships between ink traps and color differences in two-color solid overprints. The specimens were printed under four different conditions that the overprinting ink sequence of M(Magenta) or C(Cyan) and the overprinting method of W(Wet-on-Wet) or D(Wet-on-Dry) were changed altermately, that is M+C-W or C+M-W and M+C-D or C+M-D.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.9-16
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• 2018

Images with lower illumination from the light source or with dark regions due to shadows, etc., can improve subjective image quality by using retinex-based image enhancement schemes. The retinex theory is a method that recognizes the relative lightness of a scene, rather than recognizing the brightness of the scene. The way the human visual system recognizes a scene in a specific position can be in one of several methods: single-scale retinex, multi-scale retinex, and multi-scale retinex with color restoration (MSRCR). The proposed method is based on the MSRCR method, which includes a color restoration step, which consists of three phases. In the first phase, the existing MSRCR method is applied. In the second phase, the dynamic range of the MSRCR output is adjusted according to its histogram. In the last phase, the proposed method transforms the retinex output value into the display dynamic range using a logarithm transformation function considering human visual system characteristics. Experimental results show that the proposed algorithm effectively increases the subjective image quality, not only in dark images but also in images including both bright and dark areas. Especially in a low lightness image, the proposed algorithm showed higher performance improvement than the conventional approaches.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1132-1137
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• 2011

In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

• Restorative Dentistry and Endodontics
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• v.46 no.4
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• pp.51.1-51.13
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• 2021

Objectives: This study aimed to evaluate the effect of improper positioning single-peak and multi-peak lights on color change, microhardness of bottom and top, and surface topography of bulk fill and incremental composites after artificial aging for 1 year. Materials and Methods: Bulk fill and incremental composites were cured using multi-peak and single-peak light-emitting diode (LED) following 4 clinical conditions: (1) optimal condition (no angulation or tip displacement), (2) tip-displacement (2 mm), (3) slight tip angulation (α = 20°) and (4) moderate tip angulation (α = 35°). After 1-year of water aging, the specimens were analyzed for color changes (ΔE), Vickers hardness, surface topography (Ra, Rt, and Rv), and scanning electron microscopy. Results: For samples cured by single-peak LED, the improper positioning significantly increases the color change compared to the optimal position regardless of the type of composite (p < 0.001). For multi-peak LED, the type of resin composite and the curing condition displayed a significant effect on ΔE (p < 0.001). For both LEDs, the Vickers hardness and bottom/top ratio of Vickers hardness were affected by the type of composite and the curing condition (p < 0.01). Conclusions: The bulk fill composite presented greater resistance to wear, higher color stability, and better microhardness than the incremental composite when subjected to improper curing. The multi-peak LED improves curing under improper conditions compared to single-peak LED. Prevention of errors when curing composites requires the attention of all personnel involved in the patient's care once the clinical relevance of the appropriate polymerization reflects on reliable long-term outcomes.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.361-368
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• 2018

As autonomous driving research is rapidly developing, pedestrian detection study is also successfully investigated. However, most of the study utilizes color image datasets and those are relatively easy to detect the pedestrian. In case of color images, the scene should be exposed by enough light in order to capture the pedestrian and it is not easy for the conventional methods to detect the pedestrian if it is the other case. Therefore, in this paper, we propose deep neural network (DNN)-based multi-spectrum pedestrian detection method using color and thermal images. Based on single-shot multibox detector (SSD), we propose fusion network structures which simultaneously employ color and thermal images. In the experiment, we used KAIST dataset. We showed that proposed SSD-H (SSD-Halfway fusion) technique shows 18.18% lower miss rate compared to the KAIST pedestrian detection baseline. In addition, the proposed method shows at least 2.1% lower miss rate compared to the conventional halfway fusion method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• 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.

• Journal of the Korean Institute of Rural Architecture
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• v.14 no.2
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• pp.67-74
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• 2012

This study investigated that grasped the present state of high-rise apartment on Urban Street color, through the color image estimation effect of primary factor on color image preference. The range of study were high-rise apartment on Urban Street color of land for housing, Sangmu, Woonnam, Shinchang, Pungam, Ilgok, Moonheung district. The method of study put out a model of reference after photography a spot colorimeter BIB test. And the data analyzing was factor analysis, multi regression through Semantic Differential Method, questionnaire. The result of study, the present state of color was used predominate, support color is YR, Y, and stress color is YR, R. Predominate color showed distribution of high luminosity, low freshness and assistance, stress color is middle luminosity, low freshness. And effects of primary factor on color image preference were 'unification', 'comfortableness', 'sophistication'. The result of this study showed that need high luminosity color for comfortableness to improve of high-rise apartment on Urban Street color, harmony of color, harmony of vertical horizontality color scheme pattern, consult square rate of stress color.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.590-598
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• 2017

Recently, there has been an increase in the number of hazardous events, such as fire accidents. Monitoring systems that rely on human resources depend on people; hence, the performance of the system can be degraded when human operators are fatigued or tensed. It is easy to use fire alarm boxes; however, these are frequently activated by external factors such as temperature and humidity. We propose an approach to fire detection using an image processing technique. In this paper, we propose a fire detection method using multichannel information and gray level co-occurrence matrix (GLCM) image features. Multi-channels consist of RGB, YCbCr, and HSV color spaces. The flame color and smoke texture information are used to detect the flames and smoke, respectively. The experimental results show that the proposed method performs better than the previous method in terms of accuracy of fire detection.