人眼瞳孔大小的检测技术在医学领域具有较大的研究和应用意义。采用图像处理技术开展了瞳孔大小的检测算法研究, 通过对瞳孔图像进行预处理、获取图像处理区域、边缘检测、链码编码算法识别瞳孔边界、改进Hough圆拟合瞳孔及大小计算, 实现了瞳孔大小的检测功能。通过对正常人眼瞳孔图像以及病变瞳孔图像检测的实验分析, 算法实现的瞳孔拟合覆盖率达到85%以上, 检测时间短, 易于在实时系统中应用。

The detection technique of pupil size has great significance in medical field. The algorithms for pupil size detection was studied by using image processing technology. By mkaing pre-processing on pupil images, acquiring the image processing area, edge detection, recognizing the pupil boundary with encoding chain and coding, and improving Hough circle to fit the pupil size, the detection on pupil size can be realized. Based on the detections on normal pupil images and diseased pupil images, the system can reach a pupil fitting coverage rate of 85%, and the detection only consumes a very short time, making it can be easily applied in practice.