CAJ | 학술논문

在疲劳驾驶研究中，人脸图像的提取至关重要，所提取图像的质量直接影响到后续图像处理和最终疲劳度判定。通过肤色采样统计和聚类分析，确定一种在YCbCr 空间下的高斯模型肤色分割方法，即把图像转换到YCbCr 颜色空间，压缩肤色分布范围，使图像亮度和色度分离。其后，应用聚类思想的最大类间方差Otsu算法，通过选取最佳动态阈值对肤色区域进一步细致分割，实现人脸区域的准确定位。
재피로가사연구중，인검도상적제취지관중요，소제취도상적질량직접영향도후속도상처리화최종피로도판정。통과부색채양통계화취류분석，학정일충재YCbCr 공간하적고사모형부색분할방법，즉파도상전환도YCbCr 안색공간，압축부색분포범위，사도상량도화색도분리。기후，응용취류사상적최대류간방차Otsu산법，통과선취최가동태역치대부색구역진일보세치분할，실현인검구역적준학정위。
In the researches of fatigue driving ,face image extraction is very important because the image quality may influence the subsequent image processing and eventual fatigue degree determination .By color sampling and clustering analysis , Gauss model skin color segmentation method under the YCbCr space is studied here .First the image is converted to YCbCr color space for color range compression and image luminance and chrominance separation . Then with the Otsu segmentation method ,more detailed segmentation for color region is obtained by choosing the optimal dynamic threshold to realize the accurate face region positioning .