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An Automatic Focusing Algorithm

机译:自动聚焦算法

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摘要

A simple and effective automatic focusing algorithm is proposed in this article. The principle of the proposed automatic focusing algorithm is based on that, for the radial test pattern, a best-focused image should have the smallest blurred region in the middle of the acquired image, and hence, should have the smallest equivalent radius. The circular Hough transform has became a common method in numerous image-processing applications for circle detection. Various modifications to the basic circular Hough transform have been suggested, such as: the inclusion of edge orientation, simultaneous consideration of a range of circle radii, the use of a complex accumulator array with the phase proportional to the log of the radius, or for filter operations. The purpose of this work is to show that a radius of a circular region extracted by a normalized circular Hough transform is a possible solution for determining the sharpness of images. To acquire high quality images with a given CCD camera, it is crucial that the camera be located exactly at the back length of the lens, i.e., the focus position of the lens. In the best conditions, the contours of the acquired images are of the sharpest, with none of the blurring effects associated with unfocused images. Acquiring such high quality images by these means is the main goal of the automatic . focusing algorithm proposed in this article.
机译:本文提出了一种简单有效的自动聚焦算法。所提出的自动聚焦算法的原理是基于这样的:对于径向测试图案,最佳聚焦的图像应该在所获取图像的中间具有最小的模糊区域,因此应该具有最小的等效半径。圆形霍夫变换已成为许多用于圆检测的图像处理应用程序中的常用方法。已建议对基本的圆形霍夫变换进行各种修改,例如:包括边缘方向,同时考虑圆半径范围,使用相位与半径对数成正比的复杂累加器阵列,或者过滤操作。这项工作的目的是表明,通过归一化的圆形霍夫变换提取的圆形区域的半径是确定图像清晰度的可能解决方案。为了用给定的CCD照相机获取高质量的图像,至关重要的是照相机必须精确地位于镜头的后部长度,即镜头的聚焦位置。在最佳条件下,所采集图像的轮廓最清晰,没有模糊效果与未聚焦图像相关。通过这些手段获得如此高质量的图像是自动装置的主要目标。本文提出的聚焦算法。

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