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亮度图像的阈值

[英]Thresholding in luminance image

原文 2017-07-22 04:22:29 9 1 java/ opencv/ image-processing/ ocr/ threshold

I have an image that contains an illuminate. 我有一个包含照明的图像。 First I crop the area which I want to process then convert it into the binary image. 首先，我裁剪要处理的区域，然后将其转换为二进制图像。 I use Otsu's thresholding, but it gives a bad result for this problem. 我使用了Otsu的阈值设置，但此问题的结果很糟糕。 I have to try to use adaptive threshold, but this method dependent on block size and C parameter (opencv method). 我必须尝试使用自适应阈值，但是此方法取决于块大小和C参数（opencv方法）。 What should I do to get a good result in this problem? 我应该怎么做才能在这个问题上取得好的结果？

Original image, but I crop the certain area 原始图片，但我裁切了特定区域 : ：

Otsu Thresholding result 大津阈值结果

1 个解决方案

adaptive threshold in not suitable for your case. 自适应阈值不适合您的情况。 if you like to simply create a binary image with black background and white text (or vise-versa), and you have tight cropped area, you can simply do below steps: 如果您只想创建带有黑色背景和白色文本（或反之亦然）的二进制图像，并且裁切区域很紧，则可以执行以下步骤：
1-convert image to gray scale 1将图像转换为灰度
2-normalize your image (ignore 1% of darkest and lightest pixels) 2标准化您的图像（忽略最暗和最亮像素的1％）
3-use a fixed threshold (something between 0.3 to 0.7) 3-使用固定阈值（介于0.3到0.7之间）
4-do some morphological enhancement like eroding, dilating, opening and closing for eliminating noise. 4-做一些形态上的增强，例如腐蚀，扩张，打开和关闭以消除噪音。
adaptive thresholding used in case of uneven luminance when you have a gradient light on board which is not present in you example. 当您的示例中不存在梯度光时，在亮度不均匀的情况下使用自适应阈值。