First off thank you for providing such a useful program, Cell Profiler is a great resource and will hopefully be playing a large roll in my research. I am using the program for its straightforward image analysis pipeline and integration to matlab, however I am not using it to analyze cells. I am colelcting timelapse pictures of snow accumulation on solar panels with the goal of characterizing snow shedding performacne of panels. As such, I have a photograph of a field of panels, and have created a binary mask image to locate each panel in the frame. After masking each panel I threshold each masked panel seperately using otsu threshold with a minimum set at 0.5. Generally speaking, I am looking for white snow on a black panel, and therefore there is a clear seperation, however on some overcast or snowy days the contrast between panel and snow is not that great, thus my desire to use an adaptive algorithm.
The issue I am running into is that the Otsu thresholding will consistantly choose the 0.5 threshold, and what I suspect is happening is it is averaging over the entire photograph, which is weighted heavily black after the mask operation, casuing the algorighm to always jump to its lowest threshold value. Is there a way of making the threshold operation consider only the area inside of the mask when performing its weighting? Or is this already happening and do I have another issue?
I’ve attached my pipeline
Thanks for your help
Queen’s Applied Sustainability Group
ThresholdtestbatchPIPE.cp (49.9 KB)