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paperless Searchable Hand-Written Note Protocol for EN

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My apologies if this topic has been covered previously; I could not seem to find a firm answer via the search functions, so here I am.

I am a new premium user after a year on Evernote, and I recently made the paperless plunge with the addition of a Scansnap 1500 on a Windows platform. I have a boat load of archived and frequently reviewed hand-written (not cursive, usually) notes that, if possible, I would like to get into a searchable format within EN. I would also like to maintain a filing structure outside of EN for these scanned documents, for both backup and non-Endnote sharing purposes.

My process to this point for scans of digital documents (primary source journal articles, book chapters, proceedings, etc.) has been:

  • scan to high quality PDF into my desktop "inbox" folder (purged at least daily)
  • Rename PDF as per my system
  • OCR with Acrobat X Pro
  • Save as optimized PDF
  • Import to my "collection box" within EN and tag/note away.
  • (aside) then move the pdf to a cloud-synced and locally backed up folder structure

Is there any merit to scanning hand-written (ink and paper) documents as jpegs? I did a trial on some older lecture notes and found that although the EN OCR function performed very well for keyword searches, relying on the EN solution leaves my non-EN notes unsearchable. I would love to minimize even my current process as much as possible while retaining as many options for the files outside of EN. Unless I was missing something, scanning multi-page written notes as images also requires one to aggregate the separate pages into one document to be uploaded as a note; this is a bit of a turn-off as well.

I have gotten so much from these forums already, so thank you all, and I look forward to any responses.

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Evernote uses one OCR/indexing app for PDFs & another for images:

Be sure when you're sending the [handwritten] notes to Evernote that they are in image format. If you're sending them as PDFs, the PDF OCR/index app doesn't work well with handwriting. Handwriting is better indexed when it's in image format b/c the OCR/index will create a tree of possibilities.

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Very well.

Given that the goal would be having an OCR copy of the document (image OR pdf) both in and outside of Evernote, could you walk me through what you envision the steps to be, beyond what I listed in the OP? How would one treat images differently from PDFs or other text notes?

And if I am asking a question that has been comprehensively covered elsewhere, by all means, post a link and I'll check it out before troubling you further.

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Alternatively, Evernote could have a simplified, standardized handwritten alphabet (like Palm's Graffiti, but hopefully more readable by human eyes) that the OCR can hack. This would be cool beyond words.

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The "backbone" of Evernote has been our handwriting recognition from day one. That's where we got our start, what sets us apart, and our R&D guys work tirelessly every day to improve on it. That's not to say our other stuff isn't awesome, but hey - who else can recognize "Happy Birthday" written in frosting on a cake?

You'll get the best results if you scan handwritten documents in as .jpgs at the around 600DPI, with a good contrast (ink should stand out clearly from the background, and not blend in with wrinkles in the paper, lined paper, etc, crazy ink colors [scan in black and white if you have a tendency to switch between green/pink/blue/purple/sparkle/etc], light pencil marks, etc.) Also, we look for text at +-5 off 90/180 degrees, so try to put the "text" of the paper in as straight as possible, even if that means your paper will be scanned at a skew.

If you're doing this and you're still not getting results, file a support request via the link in our signature and ask us for a JPG recognition check. We'll analyze your images and give you specific tips on how to make your scans come through better before you go whole-hog into your project, as well as get that aforementioned R&D team something else to work on for the future.

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Heather,

Thank you for the straightforward instructions. I will run a few trials on a representative sample, then re-evaluate. Just to make sure that I am following your recommendations correctly, I would like to know if you suggest uploading these .jpgs as individual images/notes, or whether combining them into a single PDF before uploading would affect the Evernote handwriting recognition process? If so, would saving as an "optimized PDF" in Acrobat affect the efficacy of recognition also?

Most of these written documents are multi-pagers.... some of the resulting files at 600 dpi are quite large; it goes without saying that if one can conserve bandwidth while preserving the handwriting recognition ability, that would be the preferred option.

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Alternatively, Evernote could have a simplified, standardized handwritten alphabet (like Palm's Graffiti, but hopefully more readable by human eyes) that the OCR can hack. This would be cool beyond words.

That would be about fifty steps backwards, IMO.

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You can experiment - depending on how clear the image is, 300DPI should work fine.

Converting them to PDF would not be recommended, as we use different recognition engines for JPG and PDF. Our Handwriting recognition is much more accurate over JPG. However, you can add multiple JPGs to the same note.

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The "backbone" of Evernote has been our handwriting recognition from day one. That's where we got our start, what sets us apart, and our R&D guys work tirelessly every day to improve on it. That's not to say our other stuff isn't awesome, but hey - who else can recognize "Happy Birthday" written in frosting on a cake?

You'll get the best results if you scan handwritten documents in as .jpgs at the around 600DPI, with a good contrast (ink should stand out clearly from the background, and not blend in with wrinkles in the paper, lined paper, etc, crazy ink colors [scan in black and white if you have a tendency to switch between green/pink/blue/purple/sparkle/etc], light pencil marks, etc.) Also, we look for text at +-5 off 90/180 degrees, so try to put the "text" of the paper in as straight as possible, even if that means your paper will be scanned at a skew.

If you're doing this and you're still not getting results, file a support request via the link in our signature and ask us for a JPG recognition check. We'll analyze your images and give you specific tips on how to make your scans come through better before you go whole-hog into your project, as well as get that aforementioned R&D team something else to work on for the future.

A little off topic but worth mentioning, this is very cool! Where else can you get a direct, helpful response to a user issue/concern other than EN? This is just one of the many reasons I love EN!!

I'm glad this topic was brought up. I'm thinking of adding handwritten notes to my work flow, especially considering I'm thinking of going back to school. I'm going to give this a try.

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Slightly off topic -- I'm investigating handwriting note taking programs on the iPad, but I'm looking for a good one that "integrates" with Evernote. Most of them will "send to" EN, but that's an additional step in the work flow that I'd rather not take.

  1. Is there any way to have handwritten notes from any of these apps simply get saved into Evernote?
  2. What are the best handwriting note apps? Any that will convert handwriting to text?

Thanks.

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Slightly off topic -- I'm investigating handwriting note taking programs on the iPad, but I'm looking for a good one that "integrates" with Evernote. Most of them will "send to" EN, but that's an additional step in the work flow that I'd rather not take.

  1. Is there any way to have handwritten notes from any of these apps simply get saved into Evernote?
  2. What are the best handwriting note apps? Any that will convert handwriting to text?

Thanks.

While I do not own an iPad (though I would enjoy having one and after reading about various uses am considering), I do like what I've read about Penultimate. This Webpage describes integration with Evernote which might meet your expectations.

http://willkelly.org/2012/01/22/penultimate-evernote-finally-together/

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