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Half and Full Helmet Wearing Detection in Thailand using Haar Like Feature and Circle Hough Transform on Image Processing

机译:泰国的一半和全头盔佩戴检测使用哈尔像特征和圈子跳跃变换在图像处理上

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摘要

Helmet detection has a wide area of applications in image processing. A new helmet detection technique is proposed in this paper. The technique combines two methods for helmet detection to achieve better detection rates. The two methods are face detection using haar like feature for detection between without helmet and full helmet and circle hough transform for detection between without helmet and half helmet. In the first module of the technique, we proposed a fast algorithm for detecting helmet in color images. The algorithm uses haar like feature to detect helmet regions, that, face/ nose/ mouth/ left eye/ right eye detection method can not detection between full and half helmet. So, the second module of the technique, the circle hough transform is applied for detection it. In experiments on images, our technique has achieved high detection rates and low false positives due to the application of the new algorithm.
机译:头盔检测在图像处理中具有广泛的应用领域。本文提出了一种新的头盔检测技术。该技术结合了两种用于验证的头盔检测方法以实现更好的检测率。这两种方法是使用HAAR的面部检测,如没有头盔和完整头盔和圆形转换,用于在没有头盔和半头盔之间检测的圈子变换。在该技术的第一模块中,我们提出了一种用于检测彩色图像头盔的快速算法。该算法使用HAAR类似于检测头盔区域,即面部/鼻子/嘴/左眼/右眼检测方法无法检测到完全和半头盔之间。因此,该技术的第二模块,圆霍夫变换应用于检测。在图像实验中,由于应用新算法,我们的技术已经实现了高检测率和低误报。

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