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A Novel Binarization Method to Remove Verdigris from Ancient Metal Image

机译:一种新的二值化方法,从古代金属形象中移除Verdigris

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Nowadays, preserving the knowledge from the ancient metal image has become a tedious process. In ancient temples and old Illams, many important scripts are written on the metal images, due to aging, verdigris, dirt, color change and variation in atmospheric temperature, pressure and humidity, where the images degrade the visual impact of the letters present in them. These types of degradation challenges can be obtained by using image binarization. The proposed novel method effectively removes the degradation from metal images. The degraded metal image is passed to Fast NL means denoising method, which converts the resultant image as gray scale and increases the contrast enhancement, wherein the contrast enhanced image is placed for edge detection and applied an adaptive thresholding. The thresholded image is passed to a morphological open in post enhancement stage to finally obtain the output image by which all types of degradations are removed. Proposed method is giving the exceptional accuracy of about 95.98%.
机译:如今,保护古代金属形象的知识已成为一个繁琐的过程。在古老的寺庙和旧伊兰德,许多重要剧本都是写在金属图像上,由于衰老,verdigris,污垢,颜色变化和大气温度,压力和湿度的变化,图像降低了存在的字母的视觉影响。通过使用图像二值化可以获得这些类型的劣化挑战。所提出的新方法有效地去除金属图像的降解。降级的金属图像被传递到快速NL意味着去噪方法,其将所得图像转换为灰度级并增加对比度增强,其中对比增强图像被放置用于边缘检测并施加自适应阈值。阈值图像被传递到后增强阶段中的形态开放,以最终获得输出图像,通过该输出图像被移除所有类型的降级。提出的方法具有约95.98%的特殊准确性。

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