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createERFilterNM1 - Parameter

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I'm using the Scene Text Detection features of OpenCV and have some troubles finding the optimal parameters for createERFilterNM1. Here is what the [doc](http://docs.opencv.org/3.0-beta/modules/text/doc/erfilter.html#createerfilternm1) states: > C++: Ptr createERFilterNM1(const Ptr&> cb, int thresholdDelta=1, float minArea=0.00025, float maxArea=0.13,> float minProbability=0.4, bool nonMaxSuppression=true, float> minProbabilityDiff=0.1 ) Parameters: >> - cb – Callback with the classifier. Default classifier can be implicitly load with function loadClassifierNM1(), e.g. from file in > samples/cpp/trained_classifierNM1.xml> - thresholdDelta – Threshold step in subsequent thresholds when extracting the component tree > - minArea – The minimum area (% of image size) allowed for retreived ER’s > - maxArea – The maximum area (% of image size) allowed for retreived ER’s > - minProbability – The minimum probability P(er|character) allowed for retreived ER’s > - nonMaxSuppression – Whenever non-maximum suppression is done over the branch probabilities > - minProbabilityDiff – The minimum probability difference between local maxima and local minima ERs The default values are not the same as in the [example](https://github.com/Itseez/opencv_contrib/blob/master/modules/text/samples/textdetection.cpp). So I wonder what the optimal settings are. Would it be possible to optimize the settings when I know the fontsize of the to-detect-text? Maybe by setting the max/minArea to the size of a letter? Keeping this in mind I tried to tweak the settings a bit to get text detection for this [image](http://i.imgur.com/GiaL63K.png) to work (I would like to detect the subtitles). With thresholdDelta = 16, minArea = 0.0004 maxArea = 0.04 I get these [results](http://i.imgur.com/562zf78.png). Changing minProbability and minProbabilityDiff seems to change nothing. But maybe it's no use given the quality of the source image. I lack the clear understanding of the parameters. Could someone please explain the parameters more in detail for me or give some hints on how to find the optimal parameters?

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