• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.945-961
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• 2019

Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.162.4-162
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• 2001

This paper presents a fuzzy-based method for classification skin color object in a complex background under varying illumination Parameters of fuzzy rule base are generated using a genetic algorithm(GA). The color model is used in the YCbCr color space. We propose a unique fuzzy system in order to accommodate varying background color and illumination condition This fuzzy system approach to skin color classification is discussed along with an overview of YCbCr color space.

• The Journal of the Korea Contents Association
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• v.3 no.1
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• pp.58-63
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• 2003

In this paper, an object tracking system in a known environment is proposed. It extracts moving area shaped on objects in video sequences and decides tracks of moving objects. Color invarianoe features are exploited to extract the plausible object blocks and the degree of radial homogeneity, which is utilized as local block feature to find out the block correspondences. The experimental results are given.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.101-109
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• 2002

In this paper, multiple object tracking system in a known environment is proposed. It extracts moving areas shaped on objects in video sequences and detects racks of moving objects. Color invariant co-occurrence matrices are exploited to extract the plausible object blocks and the correspondences between adjacent video frames. The measures of class separability derived from the features of co-occurrence matrices are used to improve the performance of tracking. The experimented results are presented.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2011-2025
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• 2021

In high-resolution satellite image classification, when the color values of pixels belonging to one class are different, such as buildings with various colors, it is difficult to determine the color information representing the class. In this paper, to solve the problem of determining the representative color information of a class, we propose a method to divide the color channel of HSV (Hue Saturation Value) and perform object-based classification. To this end, after transforming the input image of the RGB color space into the components of the HSV color space, the Hue component is divided into subchannels at regular intervals. The minimum distance-based image classification is performed for each hue subchannel, and the classification result is combined with the image segmentation result. As a result of applying the proposed method to KOMPSAT-3A imagery, the overall accuracy was 84.97% and the kappa coefficient was 77.56%, and the classification accuracy was improved by more than 10% compared to a commercial software.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.83-92
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• 2009

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.

• Korean Journal of Cognitive Science
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• v.28 no.1
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• pp.27-42
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• 2017

Stroop effect(Stroop, 1935) is a reliable paradigm which has been used in various psychological research. Although classic Stroop experiment used color and color name for experimental stimuli, subsequent research reported that a color(e.g. green) and an object(e.g. grass) which displays a typical color show similar effects depending on color-object congruency(Klein, 1964). Because past research that used Stroop effect to investigate semantic representation tested association between concrete object and color, they predominantly used concrete nouns and their corresponding color names as stimuli(e.g. Dalrymple-Alford, 1968, 1972; Klein, 1964). Recently, Sherman and Clore(2009) reported that response time to white or black words is affected by moral value of words (e.g., honesty, crime) even when the words do not have specific referents. Based on this result, we tested association between thermesthesia-related adjectives(e.g., 따스한, 냉정한) and color(warm color, cold color) using Stroop task. The results showed that subjects were faster in their response to color when adjective-color was congruent than when incongruent, and there was an interaction between color and meaning of adjectives. The Stroop effect in this research is unique because, contrary to previous research that used concrete nouns, the effect was obtained even with abstract adjectives which do not have specific referents. In addition, unlike Sherman and Clore(2009) that used achromatic color, our results show that Stroop effect obtains between abstract adjectives and chromatic color.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.59-65
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• 2004

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

• Proceedings of the Korean Printing Society Conference
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• 1998.10a
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• pp.16-21
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• 1998

Spectral reflrectance of the object should be mesured to predict the color of object under various illuminants. The spectral reflectance can be represented in a multidemensional space; Generally we can obtain only three-channel data from input device such as CCD camera, color scanner etc. The estimation from three dimernsional to multidimension can be achieved using principal components of spectral reflectance. In this paper, A method to predict the spectral reflectance of skin color taken by 3-channel input device is discribed. To confirm this method, we simulate color represent under various illuminants about yellow, white and colored women face.

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.263-269
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• 2009

An object's color and intensity are determined by its spectral reflectance and illumination. Therefore, the illumination plays a key role in forming the appearance of the object in a scene. In this paper, we focus on color distinction of objects and derive the optimal illumination conditions to maximize the distance between objects in the RGB color space. As a practical approach the optimal illumination is composed by deriving the optimal linear combinations given a set of LED light sources. The effectiveness of our approach is shown through experimental results using an endoscope system.