I am completely new to image processing and python. I hope I can find some help here. I am trying out a project on detecting fouling% on a ship hull using raspberry pi. I am trying to learn how this going to be done and how can i pre-process these images. Images will be captured underwater using Picam module and purpose of stitching is to generate an overview of overall fouling and to calculate the percentage of fouling. Below are ways I will approach this problem, but am I right to say haarcascade will not be able to use in this project because it is not possible to use it to calculate percentage of fouling?

To classify type of fouling and percentage of fouling

Macro fouling and microfouling pictures added and trained using Haarcascade or PCA algorithm to identify them OR Colour Segmentation/blob detection. The final result can be then obtain accurately in comparison to manual image segmentation like Grabcut algorithm.

  • $\begingroup$ Welcome to DSP.SE! Your question is on-topic for this site, but it seems like there are two or three questions here, and it's not clear (to me) exactly what question you're asking. Can you edit your question, and pare it back to a single question? Perhaps the first step in the application that you're having problems with? It might also be good to explain what your image acquisition system is, and why you have to stitch a panorama together. $\endgroup$
    – Peter K.
    Commented Dec 11, 2015 at 17:41
  • $\begingroup$ @PeterK. Thanks for the advice Peter! Have narrowed down my question. $\endgroup$
    – Jeremy.J
    Commented Dec 11, 2015 at 18:09


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