• Korean Institute of Interior Design Journal
• /
• v.21 no.1
• /
• pp.40-50
• /
• 2012

This study aims at suggesting the applicability of color combination based upon the characteristics of environmental color perception and the nuance concept of Natural Color System(NCS). The results are summarized below: First, NCS is a scientific coloring system in consideration of the relevance between people, light and environment, to be based on a phenomenological point of view. NCS can be called a psychometric model reflecting our natural color sense. Second, the color triangle established by NCS is one of the methods of expression based on the human visual mechanism, which is classified by two attributes of hue and nuance, not by the three color attributes of hue, lightness and saturation. The nuance concept of NCS implies the impression, atmosphere and tone that are perceived in colors, which are related to lightness and saturation. Accordingly, this paper suggests that the coloring arrangement emphasizing nuance and tone is more useful than hue in color planning. Third, aesthetic impression in environmental color perception is inclusive of instantly perceptive nuance, which is connected with affordance. The affordance is revealed by the different relation of similarity. In this regard, a strong relationship is noticed between color combination and the sense of pleasantness. The hypothesis regarding the complementation and similarity of contrasting nature is judged to provide observers with aesthetic order. Finally, this paper also suggests four harmonizing methods in the NCS color triangle based upon equal blackness, equal whiteness, equal chromaticness and same nuance. At the same time, opposition and a different concept of hue, lightness and lightness are combined complementarily with the nuance value to suggest patterns of color combination.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.1123-1127
• /
• 2005

The Conventional methods of color separation in computer-based machine vision offer only weak performance because of environmental factors such as light source, camera sensitivity, and others. In this paper, we propose an improved color separation method using RGB, HLS, color coordination space, and fuzzy similarity measure. RGB consists of red, green and blue, the three primary colors of light. HLS includes hue, light and saturation, the human recognition elements of co]or. A fuzzy similarity measure was employed for evaluate the similarity among fuzzy colors with the six features of RGB and HLS.

• Journal of information and communication convergence engineering
• /
• v.11 no.1
• /
• pp.62-68
• /
• 2013

This paper proposes a method for identification of harmful video images based on the degree of harmfulness in the video content. To extract harmful candidate frames from the video effectively, we used a video color extraction method applying a projection map. The procedure for identifying the harmful video has five steps, first, extract the I-frames from the video and map them onto projection map. Next, calculate the similarity and select the potentially harmful, then identify the harmful images by comparing the similarity measurement value. The method estimates similarity between the extracted frames and normative images using the critical value of the projection map. Based on our experimental test, we propose how the harmful candidate frames are extracted and compared with normative images. The various experimental data proved that the image identification method based on the 2-dimensional projection map is superior to using the color histogram technique in harmful image detection performance.

• Journal of KIISE:Software and Applications
• /
• v.34 no.1
• /
• pp.1-10
• /
• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• Journal of Plant Biotechnology
• /
• v.3 no.3
• /
• pp.145-149
• /
• 2001

This study was conducted to analyze the morphological characteristics such as flower color, flower type, flower diameter and flower stalk, and the main annual production yield, and genetic similarity of twenty four Gerbera species growing in Korea. Most of flower colors were pink. The numerical order of flower color was pink, orange, red, double-colored, and milk-white. Majority of flower types were sin81e or semidouble flowers. A few species were double flowers. flower diameters were from 7 ㎝ to 12 ㎝, showed significant differences compared to other characteristics. Flower stalks were ranged from 55 ㎝ to 65 ㎝. Only one species was the shortest as 55 ㎝. The others were similar size as about 65 ㎝. Main annual production yields were between 190 and 400 blossoms. Fifty seven reproducible polymorphic bands from eighty primers were used for analyses of genetic similarity. The genetic similarity of 24 collected Gerberas was largely classified into five groups. The average similarity coefficient was 0.72 ranged from 0.50 to 0.90. The highest similarity coefficient was shown between 'Sardana' with red/white flower color and double flower type, and 'Tamara' with orange flower color and double flower type as 0.90.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.5197-5218
• /
• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.4
• /
• pp.586-594
• /
• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2003.05a
• /
• pp.206-207
• /
• 2003

• Journal of the Korean housing association
• /
• v.15 no.4
• /
• pp.9-16
• /
• 2004

Architectural theories in western architecture have been considered as a basis for answering the fundamental questions of architectonics: proportion, symmetry, color, harmony and so on. Among those the architectural design theory is significant, since it affects the aesthetic evaluation of human perception. This paper gives an outline in applying the traditional design principles of architecture to contemporary architecture by 'unification through similarity' of architectural components such as form, scale, texture and color. As we see from this research, unification can be achieved in a design by the combination of the four components; that is, to balance between the four above-mentioned components in buildings, through the similarity of one or more of these components.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.116-125
• /
• 2019

The fire should extinguish as soon as possible because it causes economic loss and loses precious life. In this study, we propose a new atypical fire and smoke detection algorithm using deep learning and color histogram of fire and smoke. First, input frame images obtain from the ONVIF surveillance camera mounted in factory search motion candidate frame by motion detection algorithm and mean square error (MSE). Second deep learning (Faster R-CNN) is used to extract the fire and smoke candidate area of motion frame. Third, we apply a novel algorithm to detect the fire and smoke using color histogram algorithm with local area motion, similarity, and MSE. In this study, we developed a novel fire and smoke detection algorithm applied the local motion and color histogram method. Experimental results show that the surveillance camera with the proposed algorithm showed good fire and smoke detection results with very few false positives.