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A New Method of Improving Performance of Canny Edge Detection

机译:一种提高罐头边缘检测性能的新方法

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The traditional Canny Edge Detection Method does not perform efficiently when applied to low contrast images. It creates false edges as it cannot isolate the object from the background properly while detecting edges of any image with low contrast. In response to this problem, this paper proposes a solution using which the performance of Canny Edge Detection can be improved significantly. The images subjected to edge detection is pre-processed by stretching the image histogram. Stretching the image histogram using different stretching limits results in processed images with enhanced contrast. We obtained the best result of Canny Edge Detection Method by applying the detection technique on the modified image which has the best image contrast. The edge detected images show visual proof as well as quantitative proof of the improved performance of Canny edge detection using this process.
机译:当应用于低对比度图像时,传统的Canny Edge检测方法不会有效地执行。它创造了假边缘,因为它无法正确地将对象与背景隔离,同时检测具有低对比度的任何图像的边缘。响应于这个问题,本文提出了一种解决方法,可以显着提高罐内边缘检测的性能。通过拉伸图像直方图预处理经过边缘检测的图像。使用不同的拉伸限制伸展图像直方图导致具有增强对比度的处理图像。我们通过在具有最佳图像对比度的修改图像上应用检测技术获得了Canny边缘检测方法的最佳结果。边缘检测到的图像显示了使用此过程的敏感边缘检测性能的改进性能的定量证明。

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