Enhance reliability of script in identifying an image exists in a digitised document (OpenCV)

€30-250 EUR

Completed

Posted

over 6 years ago

€30-250 EUR

Paid on delivery

I'm trying to use existing software on a project to extract printer's illustrations/ornaments/ornate letters from digitised books. To do this, I have turned to [login to view URL] which draws on OpenCV. However, the software does not reliably identify all of the images on a page; in some cases it does not recognise an illustration exists at all. Can the settings in the [login to view URL] file (attached) be changed to significantly improve the chances of identifying/extracting illustrations? For instance, [login to view URL] - the illustration is identified as something to be extracted. But [login to view URL] the image is not seen. Also, in [login to view URL] only one image is found (the ornate letter on the left) but not on the right. [login to view URL] is not seen as containing an image. [login to view URL] - software does not see any illustrated elements (though there are two). [login to view URL] no illustration is detected.

OpenCV

Python

Project ID: 15572458

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5 proposals

Remote project

Active 6 yrs ago

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Awarded to:

@earthat

HI, I checked the code of fleuron. The canny threshold is used for binarization, this is what which can be improved for better results. I can help you out in this. Relevant Skills and Experience Python: 5+ years openCV: 5+ years image binarisation Proposed Milestones €194 EUR - Complete Work Lets discuss the details in chat. My method is suitable for historical document binarisation. Check out [login to view URL] With Regards

€194 EUR in 20 days

4.8

(30 reviews)

5.6

5 freelancers are bidding on average €141 EUR for this job

@MetaoriginLab

Our dedicated team of software and programming professionals provides our clients with state of the art programming solutions in the python language. Me and my team has 5 years of experience into Python/Django,OpenCV & Data Scraping or Web Crawling. Can very well execute this Project and can work at US hours.

€248 EUR in 8 days