形态学中连通字符的图像分割 [英] image segmentation for connected character in morphology

问题描述

在我问一个类似的问题之前，我尝试使用分水岭分割所连接的字符，但效果不佳.一个星期前，我在Google搜索的stackoverflow上遇到了相同的问题，

有一些疑问

1.为什么需要将原始图像的尺寸调整为200像素，然后将其细化.

为什么不立即缩小原始图像.

2.如何提取这些分支点，并对稀疏图像应用形态学封闭.

我只知道闭合形态是侵蚀和膨胀组合操作.

关闭的垂直线需要2 * height + 1(这是结构元素的高度?)，我不知道如何设置.结构元素如何构造(3 * 3或其他?).

最后他们得到了下一张图片

我需要一些帮助，有人可以告诉我如何应用关闭操作并获得图像.谢谢.

解决方案

我已经使用前景功能和背景功能解决了这个问题.

一些在下面详细介绍此算法的人:

利用上下文知识对手写数字字符串进行分割和识别的遗传框架

用波斯语和英语对手写数字字符串进行分段.

流动的图像是我的捕获物.

前景区域和前景骨骼

背景区域和背景骨架

44的骨架图像.

基于上述特征点，我们可以构建分割449位数字的分段路径.

before i asked a same similar question,i tried using a watershed to segmentation the connected character but it does not well.a weeks ago,i get same question at stackoverflow in google search,Segmentation for connected characters, in the answer users,the author mmgp provide a solution that use a morphology method and closing operation but i not understand all.

i just thinning a image in hit-and-miss morphology.

the original image

the thinning image the big image for the thinning image (enlarge)

the 4-connectivity can split a digit 9 to individual character but 44 still connected.

i have a some of question about Segmentation for connected characters

1.why need resize the original image to 200-pixel and then thinning it.

why not thinning the original image by immediate.

2.how extract these branch points and apply a morphological closing to thinning image.

i just know the closing morphology is a erosion and dilation combine operation.

the closing's vertical line need a 2*height+1(this a structure element height?),i don't know and how setting.the structure element how to constructre(3*3 or other?).

the finally they get a following image

i need some help, someone can tell me how apply closing operation and get above a image. thanks.

解决方案

i have solved this problem use a foreground-feature and background-feature.

some of people that details about this algorithm below:

Agenetic framework using contextual knowledge for segmentation and recognition of handwritten numeral strings

Segmentation of Handwritten Numeral Strings in Farsi and English Languages.

the flowing image is my capture.

foreground-region and foreground-skeleton

background-region and background-skeleton

the skeleton image for 44.

based on the above feature-points ,we can constructing a segmentation path to split 449 digit.

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