Question

经过2到3天的搜索，我仍然找不到解决问题的方法。

我想在没有阴影的情况下创建鼠标分段。问题是如果我设法移除阴影我也删除尾部和脚部这是一个问题。阴影来自鼠标所在的竞技场墙壁。

我想从灰度图像中删除阴影，但我不知道如何做到这一点。首先，我删除了图像的背景，然后获得了以下图片。

edit1：感谢你的答案，当阴影没有碰到鼠标时效果很好。这就是我得到的结果：

来自这张原始图片：

我从tif文件中提取每个帧并为每个帧应用代码。这是我使用的代码：

for k=1:1000

    %reads image
    I = imread('souris3.tif',k);

    %first stage: perform thesholding and fill holes

    seg = I >20000;
    seg = imfill(seg,'holes');

    %fixes the missing tail problem
    %extract edges, and add them to the segmentation.
    edges =  edge(I);
    seg = seg | edges;

    %fill holes (again)
    seg = imfill(seg,'holes'); 

    %find all the connected components
    CC = bwconncomp(seg,8);

    %keeps only the biggest CC
    numPixels = cellfun(@numel,CC.PixelIdxList);
    [biggest,idx] = max(numPixels);
    seg = zeros(size(edges));
    seg(CC.PixelIdxList{idx}) = 1;

    imshow(seg);

end

我使用命令impixelinfo选择20000步骤，因为图像在uint16中，它是鼠标的平均值。

如果你想拥有tif文件，这是链接：

souris3.tif

感谢您的帮助。

Answer 1

我建议采用以下方法：

对图像进行阈值处理，并获得一个包含大部分鼠标身体但没有尾巴和腿部的面具。
使用MATLAB的imfill函数执行孔填充。在这个阶段，分割几乎是完美的，除了尾部的一部分缺失。
使用边缘图来查找尾部的边界。这可以通过将边缘图添加到分割并再次执行孔填充来完成。在这个阶段只保留最大的连接组件。

代码：

%reads image
I = rgb2gray(imread('mSWm4.png'));

%defines thersholds (you may want to tweak these thresholds, or find
%a way to calculate it automatically).
FIRST_STAGE_THRESHOLD = 70;
IM_BOUNDARY_RELEVANCE_THRESHOLD = 10;

%perform thesholding and fill holes, the tail is still missing
seg = I > FIRST_STAGE_THRESHOLD;
seg = imfill(seg,'holes');

%second stage fix the missing tail problem:
%extract edges from relevant areas (in which the matter is not too dark), and add them to the segmentation.
%the boundries of the image which are close enough to edges are also considered as edges
edges =  edge(I);
imageBoundries = ones(size(I));
imageBoundries(2:end-1,2:end-1) = 0;
relevantDistFromEdges = bwdist(edges) > IM_BOUNDARY_RELEVANCE_THRESHOLD;
imageBoundries(bwdist(edges) > IM_BOUNDARY_RELEVANCE_THRESHOLD) = 0;
seg = seg | (edges | imageBoundries);

%fill holes (again) and perform noise cleaning
seg = imfill(seg,'holes');
seg = getBiggestCC(imopen(seg,strel('disk',1)));

getBiggestCC功能：

function [ res ] = getBiggestCC(mask)
CC = bwconncomp(mask,8);
numPixels = cellfun(@numel,CC.PixelIdxList);
[~,idx] = max(numPixels);
res = zeros(size(mask));
res(CC.PixelIdxList{idx}) = 1;
end

<强>结果

每个阶段的结果：

结果图1结果：

图像2结果：

另一种观点（细分为红色）：

MATLAB-mices灰度图像中的分割，对阴影不变

1 个答案: