• Title/Summary/Keyword: Intelligent Hue Control System

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Human-Friendly Intelligent Hue Control System for Display Unit (디스플레이 장치의 인간 친화적인 지능형 색체 조절 시스템)

  • Seo, Jae-Yong;Kim, Jong-Won;Cho, Hyun-Chan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.13-18
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    • 2007
  • Human's sight holds the most extents for recognizing information among other senses. If we make much better visualized environment for human, it will become more beneficial in person's emotion or body. Human is using a lot of display units in modern society. Basic hues ate Red, Green and Blue. Using these three colors, we can change hue sense and degree of brightness of display unit. If we control hue of unit to be suitable according to individual environment, we can feel comfortable or reduce stress. In this paper, we present Human-Friendly Intelligent Hue Control System(HFIHCS) that control hue of display unit using fuzzified factors related to human's emotion and environment. The effectiveness of the proposed system is demonstrated by questionnaire.

Tongue Image Segmentation via Thresholding and Gray Projection

  • Liu, Weixia;Hu, Jinmei;Li, Zuoyong;Zhang, Zuchang;Ma, Zhongli;Zhang, Daoqiang
    • 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.