西安工程大学电子信息学院 西安 710048
TN911
College of Electronic Information, Xi’an Polytechnic University, Xi’an 710048, China
为了准确的分割出卡板上面的反应孔从而不影响和对患者病情的诊断，提出了一种基于Lab颜色空间以及HSV颜色空间的反应孔图像分割方法。根据反应孔图像的自身特点，通过在Lab颜色空间运用最大类间差进行阈值分割，在HSV颜色空间运用全局阈值法进行阈值分割，然后将分割得到的两个结果进行区域合并、滤波，最终得到目标区域。结果表明，该算法能够准确的将反应孔图像从卡板上面分割出来，并有效的抑制了噪声及光照不均带来的影响。
In order to segment reaction holes from the card, a segmentation algorithm of reaction holes based on Lab and HSV color spaces was proposed in this pepper. The method uses the means of OTSU threshold segmentation in Lab color space and global threshold segmentation in HSV according to the characteristic of reaction holes image, then combines two segmentation parts together as a whole and filters the noise, the target area was acquired finally. Experimental showed that this method can segment reaction holes precisely and restrain the influence of noise or uneven illumination.
王延年,赵朗月,刘会敏.基于混合颜色空间的反应孔图像分割算法研究[J].国外电子测量技术,2017,36(12):20-23
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