从映像中提取满足特定条件的形状 [英] Extracting Shapes that meet a certain criteria from an Image
问题描述
假设我有一个图像，我想从中提取某些形状。这个图像有很多形状，但我只关心填充对角线的形状。这样的图片可能如下所示：
由于我只关心在其中有对角线的形状，我想使用此图片生成一个如下所示：
目前，我试图用卷积来做到这一点。
我开始卷积图像与这个矩阵：
]
它产生一个看起来像的图像像这样：
这是一个相当不错的工作，提取我正在寻找的信息，但现在我想让它看起来像我理想的最终形象。
我当前过程的下一步是模糊图像，在模糊图像后，我使用一个阈值来获得这样的结果。
这非常接近我想要的，有点卡住。
你们知道更好的解决这个问题吗？最终目标是编写一个软件，它会采取任何具有这样的功能的图像，并提取这样的方式。
感谢您的时间！ p>
很好的问题。我将尝试使用ImageMagick直接从命令行 - 它安装在大多数Linux发行版，可用于OSX和Windows。它有C ++，C＃，.Net，Python，Perl，PHP等的绑定。
我会去一个具有如下的对角内核：
convert tetris.png -negate \
-morphology hit-and-miss 3x3：1,0,0 0,1,0 0,0,1result.png
一旦你有了这一点，你可能需要一种方法来找到斜线阴影区域。一种方法是将所有像素squidge集成到单个像素宽的列中 - 设想同时按在两侧，直到图片只是一个细列。你也可以做垂直的同样的事情 - 想象一个沉重的重量在图像的顶部，直到它扁平，只有一个像素高。像这样：
convert tetris.png -negate -morphology hit-and-miss3x3：1,0,0 0,1,0 0,0,1-resize 1x2200！规模25x2200！ -normalize tall.png
convert tetris.png -negate -morphology hit-and-miss3x3：1,0,0 0,1,0 0,0,1-resize 3400x1！规模3400x25！ -normalize wide.png
最后 -scale
然后你可以要求文本格式的输出，然后寻找在哪里颜色从黑色变为灰色或白色，这是形状边缘的坐标。像这样：
convert tetris.png -negate -morphology hit-and-miss3x3：1,0,0 0， 1,0 0,0,1-resize 1x2199！ -normalize -alpha off -depth 8 txt：
＃ImageMagick像素枚举：1,2199,255，灰色
0,0：（0,0,0）＃000000灰色）
0,1：（0,0,0）＃000000 gray（0）
0,2：（0,0,0）＃000000 gray（0）
0,3 ：（0,0,0）＃000000 gray（0）
0,4：（0,0,0）＃000000 gray（0）
...
...
0,184：（0,0,0）＃000000 gray（0）
0,185：（0,0,0）＃000000 gray（0）
0,186：（0,0,0） ＃000000灰色（0）
0,187：（257,257,257）＃010101灰色（1）
0,188：（3855,3855,3855）＃0F0F0F灰色（15）<=从黑色转变=
0,189：（3855,3855,3855）＃0F0F0F gray（15）
0,190：（3855,3855,3855）＃0F0F0F gray（15）
0,191：（3855,3855,3855 ）＃0F0F0F gray（15）
0,192：（3855,3855,3855）＃0F0F0F gray（15）
0,193：（3855,3855,3855）＃0F0F0F gray（15）
0,194 ：（3855,3855,3855）＃0F0F0F gray（15）
0,195：（3855,3855,3855）＃0F0F0F gray（15）
0,196：（3855,3855,3855）＃0F0F0F gray 15）
0,197：（3855,3855,3855）＃0F0F0F gray（15）
0,198：（3855,3855,3855）＃0F0F0F gray（15）
0,199：（3855,3855 ，3855）＃0F0F0F gray（15）
0,200：（3855,3855,3855）＃0F0F0F gray（15）
0,201：（3855,3855,3855）＃0F0F0F gray（15）
0,202：（3855,3855,3855）＃0F0F0F灰色（15）
...
....
0,324：（3855,3855,3855）＃0F0F0F灰色
0,325：（3855,3855,3855）＃0F0F0F gray（15）
0,326：（3855,3855,3855）＃0F0F0F gray（15）
0,327：（4883,4883,4883 ）＃131313灰色（19）
0,328：（19789,19789,19789）＃4D4D4D灰色（77）<=形状的部分
0,329：（20817,20817,20817）＃515151灰色81）
0,330：（20817,20817,20817）＃515151 gray（81）
0,331：（20817,20817,20817）＃515151 gray（81）
所以你可以看到你的形状从像素188开始，到像素328的胖部分。
此外，在原始图片上进行连接的组件分析（也称为 Blob分析）：
convert tetris.png \
-define connected-components：verbose = true \
-define connected-components：area-threshold = 100000 \
-connected-components 8 -auto-level output.png
输出
对象（id：bounding-box centroid area mean-color）：
0：3399x2199 + 0 + 0 1774.2,1149.3 5390079 srgba（255,255,255,1）
7：2045x1180 + 405 + 187 1475.1,930.4 1681486 srgba（255,255,255,1）
40：546x334 + 1753 + 1661 2025.5,1827.5 182364 srgba（255,255,255,1）
6：2057x1192 + 399 + 181 1580.7,839.8 117980 srgba（0,0,0,1）
5：702x146 + 621 + 149 971.5,221.5 102492 srgba（255,255,255， 1）
如果我在第二行输出框中绘制， / p>
convert tetris.png -stroke red -fill none -drawrectangle 405,187 2450,1367x.png
您可以查看红色边界框（1681486像素）和/或其形状（2045x1180）的区域，以考虑其比例，以及它们是否匹配您寻求的图案框的形状和大小，即它是如何是平方的，不是。
Let's say I have an image that I want to extract certain shapes from. This image has a plethora of shapes, but I'm only concerned about the shapes that are filled with diagonal lines. Such an image could look like this:
Since I only care about shapes that have diagonal lines in them, I'm trying to use this image to generate one that looks like this:
Currently, I'm attempting to do this with convolution. I start by convolving the image with this matrix: ]
Which produces an image that looks like this: This does a fairly good job of extracting the information i'm looking for, but now I want to make it look like my ideal final image.
The next step in my current process is to blur the image, and after blurring the image I use a threshold to obtain a result that looks like this.
This is very close to what I want, but I'm a little stuck. Do you guys know a better solution to this problem? The end goal is to write a piece of software that will take any image that has features like this, and extract them in this way.
Thanks for your time!
解决方案Great question. I'll have a try with ImageMagick straight from the command line - it's installed on most Linux distros and available for OSX and Windows. It has bindings for C++, C#, .Net, Python, Perl, PHP etc.
I would go for a Hit and Miss style morphology with a diagonal kernel like this:
convert tetris.png -negate \ -morphology hit-and-miss "3x3: 1,0,0 0,1,0 0,0,1" result.pngOnce you have that, you may need a method to locate the diagonally hatched area. One method is to "squidge" all the pixels into a single pixel wide column - imagine pressing in on both sides at once till the picture is just a thin column. You can also do the same thing vertically - imagine putting a heavy weight on the top of the image till it squashes flat to just one pixel tall. Like this:
convert tetris.png -negate -morphology hit-and-miss "3x3: 1,0,0 0,1,0 0,0,1" -resize 1x2200! -scale 25x2200! -normalize tall.png convert tetris.png -negate -morphology hit-and-miss "3x3: 1,0,0 0,1,0 0,0,1" -resize 3400x1! -scale 3400x25! -normalize wide.pngThe last
-scaleabove is just to make it wide enough to see - you don't need that really.You can then ask for the output in text format, and look for where the colour changes from black to a shade of grey, or white, and that is the coordinate of the edge of your shape. Like this:
convert tetris.png -negate -morphology hit-and-miss "3x3: 1,0,0 0,1,0 0,0,1" -resize 1x2199! -normalize -alpha off -depth 8 txt: # ImageMagick pixel enumeration: 1,2199,255,gray 0,0: (0,0,0) #000000 gray(0) 0,1: (0,0,0) #000000 gray(0) 0,2: (0,0,0) #000000 gray(0) 0,3: (0,0,0) #000000 gray(0) 0,4: (0,0,0) #000000 gray(0) ... ... 0,184: (0,0,0) #000000 gray(0) 0,185: (0,0,0) #000000 gray(0) 0,186: (0,0,0) #000000 gray(0) 0,187: (257,257,257) #010101 gray(1) 0,188: (3855,3855,3855) #0F0F0F gray(15) <= Transition from black = start of shape 0,189: (3855,3855,3855) #0F0F0F gray(15) 0,190: (3855,3855,3855) #0F0F0F gray(15) 0,191: (3855,3855,3855) #0F0F0F gray(15) 0,192: (3855,3855,3855) #0F0F0F gray(15) 0,193: (3855,3855,3855) #0F0F0F gray(15) 0,194: (3855,3855,3855) #0F0F0F gray(15) 0,195: (3855,3855,3855) #0F0F0F gray(15) 0,196: (3855,3855,3855) #0F0F0F gray(15) 0,197: (3855,3855,3855) #0F0F0F gray(15) 0,198: (3855,3855,3855) #0F0F0F gray(15) 0,199: (3855,3855,3855) #0F0F0F gray(15) 0,200: (3855,3855,3855) #0F0F0F gray(15) 0,201: (3855,3855,3855) #0F0F0F gray(15) 0,202: (3855,3855,3855) #0F0F0F gray(15) ... .... 0,324: (3855,3855,3855) #0F0F0F gray(15) 0,325: (3855,3855,3855) #0F0F0F gray(15) 0,326: (3855,3855,3855) #0F0F0F gray(15) 0,327: (4883,4883,4883) #131313 gray(19) 0,328: (19789,19789,19789) #4D4D4D gray(77) <= Fatter part of shape 0,329: (20817,20817,20817) #515151 gray(81) 0,330: (20817,20817,20817) #515151 gray(81) 0,331: (20817,20817,20817) #515151 gray(81)So you can see that your shape starts at pixel 188, and gets to the fat part at pixel 328.
Also, a Connected Component Analysis (also called Blob Analysis), on your original image like this:
convert tetris.png \ -define connected-components:verbose=true \ -define connected-components:area-threshold=100000 \ -connected-components 8 -auto-level output.pngOutput
Objects (id: bounding-box centroid area mean-color): 0: 3399x2199+0+0 1774.2,1149.3 5390079 srgba(255,255,255,1) 7: 2045x1180+405+187 1475.1,930.4 1681486 srgba(255,255,255,1) 40: 546x334+1753+1661 2025.5,1827.5 182364 srgba(255,255,255,1) 6: 2057x1192+399+181 1580.7,839.8 117980 srgba(0,0,0,1) 5: 702x146+621+149 971.5,221.5 102492 srgba(255,255,255,1)If I draw in the box on the second line of output, you can see it:
convert tetris.png -stroke red -fill none -draw "rectangle 405,187 2450,1367" x.pngYou might look at the area of the red bounding box (1681486 pixels), and/or its shape (2045x1180) to think about its proportions and whether they match the shape and size of your sought patterned box, i.e. how square it is or isn't.
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