[英]Recognize hand drawn shape in OpenCV
I have the following task: recognize a set of simple hand-drawn shapes on a sheet of paper from a still image (not a video stream), so they might not be exactly identically pixelwise. 我有以下任务:从静止图像(不是视频流)识别一张纸上的一组简单手绘形状,因此它们在像素方向上可能并不完全相同。
Those shapes are basically symbols for doors, windows, etc. in a floor plan (see attached image), so they might be slightly scaled or rotated (90° steps). 这些形状基本上是平面图中门,窗等的符号(请参见附图),因此它们可能会略微缩放或旋转(90°步进)。 There are about 5 different ones. 大约有5种。
So far I came across SIFT (and its OpenCV-variants SURF and ORB ) as well as a cascaded classifier to recognize haar-like features . 到目前为止,我遇到了SIFT (及其OpenCV变体SURF和ORB )以及用于识别类似haar的特征的级联分类器 。
For SIFT there seem to be too little key points in such a shape whereas I did not manage to get the haar-trained cascaded classifier to work. 对于SIFT,这种形状的关键点似乎太少 ,而我却没有设法使经过哈尔训练的级联分类器起作用。 Also, a cascaded classifier seems a bit heavy for recognizing such simple shapes, no? 另外,级联分类器对于识别这种简单形状似乎有点沉重,不是吗?
Does anyone of you have any good hints or alternative approaches? 你们中有人有什么好的提示或替代方法吗? Or maybe you even have a snippet of code lying around which I can use? 也许您甚至还可以使用一小段代码?
我认为,梯度直方图(HOG)对于此类元素应适用。
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