基于Canny算法的低分辨率图像改进数字检测

Fandi Yulian Pamuji, M. Soeleman
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引用次数: 1

摘要

本文利用Canny算法改进了低分辨率下的数字检测。随机选取低分辨率数字的数据进行算法验证。存在着许多问题,低分辨率下的图像检测率需要能够提高图像边缘检测效果的方法。在寻找在低分辨率下改变数字的正确方法时,使用一种类似于Sobel算子、拉普拉斯算子和Canny算子的算法。从实验结果中,使用Canny算子算法读取并清除低分辨率的2个数字,以下图像的MSE为3,371,PSNR为42,852,图像2的MSE为3,060,PSNR为33,350,使用Sobel算子和拉普拉斯算子。
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Improved Number Detection For Low Resolution Image Using the Canny Algorithm
Improved number detection at low resolutions using the Canny algorithm in this paper. Data from low resolution numbers are randomly selected for this algorithm’s approval. There are a number of problems, image detection rates at low resolutions are needed Methods that can improve edge detection images to get better. In finding the right way to change numbers at low resolution using an algorithm that compares like the Sobel operator, Laplacian operator, and Canny operator. From the experimental results 2 numbers in low resolution are read and clear detection using the Canny operator algorithm as the following images are MSE 3,371 and PSNR 42,852, image 2 is worth MSE 30,060 and PSNR 33,350 with these other algorithms namely Sobel operator and Laplacian operator.
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