图像增强器中视觉缺陷的自动检测

M. Kamalapriya, V. Thilagavathi
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引用次数: 0

摘要

夜视(NVD)设备图像的可见缺陷可能会造成视觉干扰,并且可能大到足以掩盖正常夜视操作的关键信息。本文提出了一种检测视觉缺陷的新方法,这将有助于评价用于图像增强器的微通道板。该方法采用圆形霍夫变换和形状分类器结合连通成分分析的混合方案。为了检测缺陷,研究了边界连通区域的统计和几何特性。根据算法的抗噪能力对性能进行评价。
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Automatic detection of visual defects in image intensifiers
Visible defects in Night Vision (NVD) Device images can act as visual distractions and may be large enough to mask critical information of normal night vision operations. In this paper we present a new method for detection of visual defects which will in turn help in the evaluation of Micro Channel Plate used in image intensifiers. The proposed method adopts a hybrid scheme using Circular Hough Transform and Shape classifier with Connected Component Analysis. The statistical and geometrical properties over a connected region of boundaries are explored for the purpose of defect detection. The performance is evaluated based on the noise withstanding capability of the algorithm.
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