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基于距离的方法可有效定位脑瘫康复中的眼球效应。

Distance-Based Method used to Localize the Eyeball Effectively for Cerebral Palsy Rehabilitation.

机构信息

Department of CSE, Sathyabama Institute of Science and Technology, Chennai, India.

Department of CSE, Jeppiaar Engineering College, Chennai, India.

出版信息

J Med Syst. 2019 Jul 2;43(8):262. doi: 10.1007/s10916-019-1405-3.

Abstract

Iris plays a vital role in human life for object identification. Many models and techniques were proposed and suggested for detecting the Iris, but the accuracy was not achieved up to the level and its frequently used for biometric application. The Proposed Work divided into two steps, at first, we detect the entire eye region outer layer by using mathematics first order derivatives by applying combinations of canny edge detection and circular hough transform. The next, we detect the inner portion of eye region that is Iris region is detected by combination of sobel edge detector and circular hough transform, As the results thereby reducing the error rate, marking the edges closest to the actual edges for maximizing the localization, indicating edges and also detect the inner and outer layer of the eye portions accurately. Finally this process is applied for cerebral palsy Children to detect the misalignment of eye and obtain the deviation position and results are compared with normal children eyes. In this context, image processing techniques are being recommended as a performance evaluation tool in cerebral palsy kids.

摘要

虹膜在人类生活中对于目标识别起着至关重要的作用。已经提出并建议了许多用于检测虹膜的模型和技术,但准确性还没有达到水平,并且经常用于生物识别应用。

所提出的工作分为两个步骤,首先,我们通过应用 Canny 边缘检测和圆形霍夫变换的组合,使用数学一阶导数来检测整个眼部区域的外层。接下来,我们通过组合 Sobel 边缘检测器和圆形霍夫变换来检测眼部区域的内部,即虹膜区域,从而减少误差率,标记最接近实际边缘的边缘以最大化定位,指示边缘并准确检测眼部的内外层。最后,将此过程应用于脑瘫儿童,以检测眼睛的错位,并获得偏差位置,并将结果与正常儿童的眼睛进行比较。在这种情况下,图像处理技术被推荐为脑瘫儿童的性能评估工具。

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