检测二进制图像中的高密度像素区域 [英] Detect High density pixel areas in a binary image

问题描述

我正在做背景减法，并且获得了带有前景物体和一些噪音的二进制图像.

I am doing background subtraction, and I obtain a binary image with foreground objects and with some noise.

我想为二进制图像上的每个对象获取ROI，然后他们对其进行分析以确保它是我想要的对象.

I want to obtain a ROI for each object on the binary image and them analyze it to ensure that is the object that I want.

如何仅分割像素强度高的区域(对象)?

How do I segment only the areas with high pixel intensity (objects)?

获得的图像的一个示例:

One example of obtained image:

推荐答案

看看openCv simpleBlobDetector，它有几个可配置的参数以及大量在线教程.

Have a look at openCv simpleBlobDetector, there are several configurable parameters to it and tons of tutorials online.

可在此处找到文档: http://docs.opencv. org/trunk/d0/d7a/classcv_1_1SimpleBlobDetector.html

或者，您也可以将白色矩形卷积在多个比例尺空间上，然后返回每个比例尺空间的中值.

Alternatively you could just convolve a white rectangle across multiple scale spaces and return the median values over each scale space.

这篇关于检测二进制图像中的高密度像素区域的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！