Detecting objects by template
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Hey, I'm working on an object detection. I have an image from multiple objects:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/161580/image.jpeg)
and want to find all screws, for example of this type:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/161582/image.jpeg)
Currently im trying to extract the screws edges using the canny algorithm. Then I want to use the generalized Hausdorff measure to search for it: http://www.cs.cornell.edu/vision/hausdorff/hausmatch.html
I'm not sure whether this is the right approach. Since I am a newbe maybe you can give me some hints for the best practices? Note that this should work for multiple objects and images. I tried using the image gradient and boundarys, too. But this failed because I could not get meaningful contours. It would be great to work with contour snippets, which would not make it neccessary to extract the whole object.
Thanks in advantage
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Image Analyst
2017-3-11
But first you'll have to extract the objects. To do that you should use better lighting, for example bottom up light, like a radiologists light box, to produce silhouettes. Or else use a broad overhead light source to eliminate shadows.
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Image Analyst
2017-3-15
Try increasing your tolerance. Also work on getting a better segmentation so that you don't have big black "bays" going into your objects. You may also have to compute a feature vector with several metrics rather than just rely on Hu's moments.
Pete McEldowney
2017-7-27
I was also trying to figure out SVD and LSF from that video too - I'm still looking but all sources are very mathematical ...
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Pete McEldowney
2017-7-27
Those holes on the bolt masks look like reflectance - either fill using code, or alter the ilghting - make it more diffuse? Or from behind the scene. Harris corner features might work OK as extra identification aids.
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