• Journal of Korea Multimedia Society
• /
• v.19 no.10
• /
• pp.1782-1791
• /
• 2016

Various color spaces such as RGB, HSV, log-chromaticity have been used in the field of person re-identification. However, not enough studies have been done to find suitable color space for the re-identification. This paper reviews color invariance of color spaces by diagonal model and explores the suitability of each color space in the application of person re-identification. It also proposes a method for person re-identification based on a histogram refinement technique and some fusion strategies of color spaces. Two public datasets (ALOI and ImageLab) were used for the suitability test on color space and the ImageLab dataset was used for evaluating the feasibility of the proposed method for person re-identification. Experimental results show that RGB and HSV are more suitable for the re-identification problem than other color spaces such as normalized RGB and log-chromaticity. The cumulative recognition rates up to the third rank under RGB and HSV were 79.3% and 83.6% respectively. Furthermore, the fusion strategy using max score showed performance improvement of 16% or more. These results show that the proposed method is more effective than some other methods that use single color space in person re-identification.

• Journal of the Korea Furniture Society
• /
• v.28 no.4
• /
• pp.294-304
• /
• 2017

The purpose of this study is to analyse and derive the color characteristics of childhood children's learning spaces and furniture for improving the color design of those and to present the direction of design and to build up the DB. The study covers products from domestic and overseas infant furniture manufacturers and 11 preschool learning rooms. The study method uses the collected furniture and spatial images to derive a palette of colors and compare color characteristics. The analysis results show that, the domestic infant furniture tend to use a variety of colors with pale tone or use consistent hard wood furniture according to the requirements of adult taste and marketability. Also, it attempts to create a very negative color scheme, but it looks like disorganized, and there is not much color design integrated with the architecture. Thus, color designs ensure that the ordering elements of the color scheme are clearly recognized by applying preferred color tones of childhood, like vivid and bright tone with high chroma and middle or hight Brightness value. Lastly, it should establish guidelines for specific palettes and color scheme, which can be utilized in the design of childhood children's learning spaces and furniture.

• Journal of Korea Multimedia Society
• /
• v.11 no.5
• /
• pp.610-622
• /
• 2008

Moving object segmentation is an essential technique for various video surveillance applications. The result of moving object segmentation often contains shadow regions caused by the color difference of shadow pixels. Hence, moving object segmentation is usually followed by a shadow elimination process to remove the false detection results. The common assumption adopted in previous works is that, under the illumination variation, the value of chromaticity components are preserved while the value of intensity component is changed. Hence, color transforms which separates luminance component and chromaticity component are usually utilized to remove shadow pixels. In this paper, various color spaces (YCbCr, HSI, normalized rgb, Yxy, Lab, c1c2c3) are examined to find the most appropriate color space for shadow elimination. So far, there have been some research efforts to compare the influence of various color spaces for shadow elimination. However, previous efforts are somewhat insufficient to compare the color distortions under illumination change in diverse color spaces, since they used a specific shadow elimination scheme or different thresholds for different color spaces. In this paper, to relieve the limitations of previous works, (1) the amount of gradients in shadow boundaries drawn to uniform colored regions are examined only for chromaticity components to compare the color distortion under illumination change and (2) the accuracy of background subtraction are analyzed via RoC curves to compare different color spaces without the problem of threshold level selection. Through experiments on real video sequences, YCbCr and normalized rgb color spaces showed good results for shadow elimination among various color spaces used for the experiments.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2002.05b
• /
• pp.136-137
• /
• 2002

• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.35 no.1
• /
• pp.99-106
• /
• 2019

This study aims to recommend the proper Color rendering index (CRI), the Correlated Color Temperature (CCT), and illuminance levels of Light-Emitting Diode (LED) lighting based on the analysis of the criteria of the current CRI, the CCT, and illuminance levels in merchandising spaces with LED lighting conditions. It would be a basic material to apply in line with user preference for LED merchandising lighting. To this end, it examines relevant literature review on the experiments designed to test whether lighting characteristics affect brightness perception, color appearance, and pleasantness. Highly saturated colors appear brighter than low saturated colors. Two lighting applications - grocery and clothing shop - were created in elaborating the effect of LED lighting characteristics of CRI on color appearance and the CCT and illuminance on pleasantness. The findings show that the criteria of CIE Ra<80 are appropriate to provide better color appearance of illuminated products in terms of LED lighting that can enhance color saturation, particularly for the red color. Furthermore, 2700 K and less than 500 lux for grocery, 4000 K and more than 500 lux for clothing shop are found to be the proper the CCT and illuminance levels respectively to bring better preference under LED lighting.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.4
• /
• pp.151-160
• /
• 2014

In this paper, a comparison of superpixel characteristics based on SLIC(simple linear iterative clustering) for several color feature spaces is presented. Computer vision applications have come to rely increasingly on superpixels in recent years. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. A superpixel is consist of pixels with similar features such as luminance, color, textures etc. Thus superpixels are more efficient than pixels in case of large scale image processing. Generally superpixel characteristics are described by uniformity, boundary precision and recall, compactness. However previous methods only generate superpixels a special color space but lack researches on superpixel characteristics. Therefore we present superpixel characteristics based on SLIC as known popular. In this paper, Lab, Luv, LCH, HSV, YIQ and RGB color feature spaces are used. Uniformity, compactness, boundary precision and recall are measured for comparing characteristics of superpixel. For computer simulation, Berkeley image database(BSD300) is used and Lab color space is superior to the others by the experimental results.

• International Journal of Computer Science & Network Security
• /
• v.23 no.5
• /
• pp.33-40
• /
• 2023

The mainstay of current image recovery frameworks is Content-Based Image Retrieval (CBIR). The most distinctive retrieval method involves the submission of an image query, after which the system extracts visual characteristics such as shape, color, and texture from the images. Most of the techniques use RGB color space to extract and classify images as it is the default color space of the images when those techniques fail to change the color space of the images. To determine the most effective color space for retrieving images, this research discusses the transformation of RGB to different color spaces, feature extraction, and usage of Convolutional Neural Networks for retrieval.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.18 no.1
• /
• pp.103-112
• /
• 2000

The color space transformation to link device-dependent color spaces and device-independent color spaces is essential for device characterization and cross-media color reproduction. There are various color conversion methods such as regression, 3D interpolation with LUT(look-up table), and neural network. In the color transformation with these methods, the conversion accuracy is essentially based on the sample data to be exploited for device characterization. In conventional method, color samples are uniformly selected in device-dependent space such as CMY and RGB. However, distribution of these color samples is very non-uniform in device-independent color space such as CIEL*a*b*. Accordingly, the conversion error in device-independent color space is irregular according to the distribution of the samples. In this paper, a color sampling method based on equi-visual perception is proposed to obtain approximate uniform color samples in CIEL*a*b* space. In order to evaluate transformation accuracy of proposed method, color space transformations are simulated using regression, 3D interpolation with LUT and neural network techniques, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.5C
• /
• pp.513-519
• /
• 2007

Color correlogram is widely used in content-based image retrieval (CBIR) because it extracts not only the color distribution of pixels in images like color histogram, but also extracts the spatial information of pixels in the images. The color correlogram uses single color space. Therefore, the color correlograms does not have robust discriminative features. In this paper, we use both RGB and HSV color spaces together for the color correlogram to achieve better discriminative features. The proposed algorithm is tested on a large database of images and the results are compared with the single color space color correlogram. In simulation results, the proposed algorithm 5.63 average retrieval rank less than single color space correlogram.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.186-188
• /
• 2005

Hand region detection in images is an important process in many computer vision applications. It is a process that usually starts at a pixel-level, and that involves a pre-process of color space transformation followed by a classification process. A color space transformation is assumed to increase separability between skin classes for hands and non-skin classes for other parts, to increase similarity among different skin tones, and to bring a robust performance under varying illumination conditions, without any sound reasonings. In this work, we examine if the color space transformation does bring those benefits to the problem of hand region detection on a dataset of images with different hand postures, backgrounds, people, and illuminations. Results indicate that best of the color space is the normalized RGB.