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首页> 外文期刊>Optical engineering >Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes
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Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes

机译：基于模糊逻辑系统的睁眼与闭眼分类的眼区分割方法

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摘要

The classification of eye openness and closure has been researched in various fields, e.g., driver drowsiness detection, physiological status analysis, and eye fatigue measurement. For a classification with high accuracy, accurate segmentation of the eye region is required. Most previous research used the segmentation method by image binarization on the basis that the eyeball is darker than skin, but the performance of this approach is frequently affected by thick eyelashes or shadows around the eye. Thus, we propose a fuzzy-based method for classifying eye openness and closure. First, the proposed method uses I and K color information from the HSI and CMYK color spaces, respectively, for eye segmentation. Second, the eye region is binarized using the fuzzy logic system based on I and K inputs, which is less affected by eyelashes and shadows around the eye. The combined image of I and K pixels is obtained through the fuzzy logic system. Third, in order to reflect the effect by all the inference values on calculating the output score of the fuzzy system, we use the revised weighted average method, where all the rectangular regions by all the inference values are considered for calculating the output score. Fourth, the classification of eye openness or closure is successfully made by the proposed fuzzy-based method with eye images of low resolution which are captured in the environment of people watching TV at a distance. By using the fuzzy logic system, our method does not require the additional procedure of training irrespective of the chosen database. Experimental results with two databases of eye images show that our method is superior to previous approaches.
机译：睁眼和闭眼的分类已经在各个领域中进行了研究，例如驾驶员的睡意检测，生理状态分析和眼疲劳测量。为了进行高精度的分类，需要对眼睛区域进行准确的分割。先前的大多数研究都使用基于图像二值化的分割方法，其依据是眼球比皮肤暗，但是这种方法的性能通常受浓密的睫毛或眼影的影响。因此，我们提出了一种基于模糊的睁眼和闭眼分类方法。首先，所提出的方法分别使用来自HSI和CMYK颜色空间的I和K颜色信息进行眼睛分割。其次，使用基于I和K输入的模糊逻辑系统对眼睛区域进行二值化处理，该方法对眼睛周围的睫毛和阴影的影响较小。通过模糊逻辑系统获得I和K像素的组合图像。第三，为了反映所有推断值对计算模糊系统输出分数的影响，我们使用修正的加权平均法，其中考虑了所有推断值的所有矩形区域来计算输出分数。第四，通过所提出的基于模糊的方法成功地进行了睁眼或闭眼的分类，该方法具有在远距离看电视的环境中捕获的低分辨率眼图。通过使用模糊逻辑系统，无论选择哪种数据库，我们的方法都不需要额外的培训过程。两个眼睛图像数据库的实验结果表明，我们的方法优于以前的方法。

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  • 来源
    《Optical engineering》 |2015年第3期|033103.1-033103.19|共19页
  • 作者

    Ki Wan Kim; Won Oh Lee; Yeong Gon Kim; Hyung Gil Hong; Eui Chul Lee; Kang Ryoung Park;

  • 作者单位

    Dongguk University, Division of Electronics and Electrical Engineering, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea;

    Dongguk University, Division of Electronics and Electrical Engineering, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea;

    Dongguk University, Division of Electronics and Electrical Engineering, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea;

    Dongguk University, Division of Electronics and Electrical Engineering, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea;

    Sangmyung University, Department of Computer Science, 7 Hongji-Dong, Jongno-Ku, Seoul 110-743, Republic of Korea;

    Dongguk University, Division of Electronics and Electrical Engineering, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Republic of Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    eye openness and closure; segmentation of eye region; image binarization; fuzzy logic system; standard deviation of vertical pixel length;

    机译：睁眼和闭眼;眼区分割图像二值化;模糊逻辑系统;垂直像素长度的标准偏差;

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