[Case Study] Stop Manual Typing Images and PDF Content

On 15th May 2025, I took on a client project that forced me to stop treating OCR as a “nice little helper” and start treating it as a core tool.

I’m a developer who often handles website content optimization and copywriting.
The client ran a beauty products business and wanted:
- Better‑optimized website content
- Proper references from PDF books related to beauty and skincare

So I had:

Several reference PDFs and book scans
Some handwritten notes
Spanish social media posts and Instagram reels as inspiration
A deadline that would not be kind if I tried to type everything manually

Typing from books and PDFs into the website would have taken hours of pure, boring manual work. Instead, I:

Took screenshots of the relevant pages/sections.
Ran them through an image to text converter (imgOCR).
Cleaned up the text a bit.
Used that text as raw material to:
- Build optimized copy
- Add references from the books
- Translate Spanish content into English for the site

Result:

I worked through 50+ images without losing my mind.
I delivered before the deadline.
I protected my reputation on the marketplace where I work.

That project convinced me: image‑to‑text isn’t just possible; used right, it’s a serious productivity boost.

So… what does “convert image to text” actually mean?

When we say “convert image to text,” we’re usually talking about:

OCR (Optical Character Recognition)
Software that reads the characters in an image (PDF pages, scans, screenshots, photos, handwritten notes) and turns them into editable, copy‑pasteable text.
AI‑enhanced OCR and post‑processing
Tools that not only extract the text, but can:
- Understand layout
- Translate it
- Summarize it
- Format it for you

For most everyday users (students, office workers, marketers, content creators, copywriters), the core question is:

Can I take what I see on screen or in a scan and turn it into clean, usable text without retyping?

In many cases: yes. In some cases: yes, but double‑check. In a few cases: don’t rely on it blindly.

Real-world ways I use image to text

Here’s how I actually use it in my daily work as a developer + copywriter.

1. Extracting content from PDFs and books

Scenario:
My client sends PDF books on beauty products and wants web copy that:

Uses ideas and wording from the books
Includes proper references and dates

Without OCR:

Manually typing paragraphs, sentences, and dates
Lots of context-switching between PDF viewer and editor
Hours of pure typing

With OCR (imgOCR):

Take screenshots of the relevant sections
Upload images in bulk:
- Free mode: 3 images per submission
- Pro mode: up to 30 images simultaneously
Export text as:
- .docx (Word)
- .txt (Notepad)
Paste into my editor, optimize, and rewrite

This turns hours of typing into minutes of selection, checking, and editing.

2. Handling handwritten samples

Some clients still send:

Handwritten notes
Corrections scribbled on paper
Rough ideas on notepads

I’ve used imgOCR to:

Extract the text from handwritten samples
Drop it straight into my content or website fields

Not every tool is good with handwriting, but imgOCR surprised me here—it handled most of it well enough that I only needed light cleanup instead of full retyping.

3. Translating social content into website copy

For one beauty products project, the client had:

Spanish Instagram posts
Screenshots from social media and reels

Workflow:

Take screenshots of posts and reels text.
Use imgOCR to extract the Spanish text.
Translate that text into English.
Use the translated text as a base for English website content.

This is especially useful when:

The client’s best-performing content is in another language.
You want to reuse the same ideas and tone, but in English.

4. Development tasks: code snippets and screenshot text

As a developer, I also run into:

Code snippets in images or PDFs
Screenshots with config values, commands, or example code

Instead of retyping:

I run the screenshot through OCR
Paste the text into my IDE
Fix any small formatting issues

It’s not perfect, but it’s usually far faster than typing line by line.

Tools I’ve actually used (and how they compare)

ChatGPT (image input)

Pros:
- Good at understanding the text (summarizing, explaining, etc.).
- Convenient if you’re already using it.
Cons (for my workflow):
- Free mode only allows one image per session.
- That’s painful when you have 50+ images.
- Not ideal when your main need is bulk extraction.

I started with ChatGPT for the beauty site project, but the one-image limit quickly became a bottleneck.

imgOCR

This is the tool that ended up doing most of the heavy lifting for me.

What I like:
- Bulk uploads:
  - Free: 3 images per submission
  - Pro: up to 30 images at once
- Good performance with:
  - Blurry or low-quality images
  - Handwritten text
  - Multilingual content
- Can export to:
  - DOCX (for editing in Word or Google Docs)
  - TXT (for quick pasting into code or CMS)
- Built‑in translation (80+ languages), which is great when working with foreign-language social content.
Free vs Pro mode (honest take):
- Free:
  - Good to test or for light use
  - Has CAPTCHA and advertisements
  - Can be a bit irritating if you’re in a rush
- Pro:
  - No ads, no captchas
  - Much better for serious, deadline-driven work
  - They offer small weekly plans, which is nice if you just have a big short-term project

My rule of thumb:
If you’re just doing a few images, free is fine.
If you care about speed and your sanity, Pro is worth it.

Picturetext.org

Also useful when you want:
- Multiple images per submission (they allow around 5)
- Quick text extraction without much friction

I see imgOCR and picturetext.org as good examples of “bulk-friendly” online OCR tools for real work.

The messy reality: where OCR can go wrong

Even with good tools, OCR is not magic. I’ve run into issues like:

1. The “O vs 0” problem

Some fonts—especially fancy or stylized fonts in books—confuse the OCR between:

The letter O
The number 0

This is dangerous when you’re dealing with:

Amounts
Dates
Codes
Reference numbers

Example issues:

A year like 2020 becomes 2O2O
A price like 1000 could turn into IOOO or similar

My rule:
If it’s anything numeric or critical (dates, prices, totals, coupon codes), I always verify manually.

2. Poor or scrambled images

If your input image is:

Very low resolution
Skewed or heavily blurred
Overlaid with patterns or watermarks

…then expect:

More recognition errors
Missed words
Wrong characters

OCR is not a miracle cure for completely broken images. Good input still matters a lot.

My typical workflow: from image to ready-to-use text

Here’s how I usually work when a client sends content in PDFs, images, or screenshots.

Collect sources
- PDFs
- Book scans
- Screenshots (social posts, reels, emails, etc.)
- Handwritten notes (photos)
Create screenshots or crop images
- Capture only the sections I really need
- Avoid including irrelevant UI or margins
Upload to imgOCR (or similar)
- For small jobs: use free mode (3 images per batch)
- For big jobs: switch to Pro for bulk (up to 30 images)
Export the text
- .docx if I want to format and edit heavily
- .txt if I just want raw text to paste into my editor or CMS
Clean and verify
- Fix line breaks and spacing
- Check:
  - Dates
  - Prices
  - Product names
  - Any numbers (especially in beauty/medical claims)
- Correct obvious OCR mistakes (O vs 0, weird symbols)
Use AI for higher-level work
- Summarize long extracted sections
- Rewrite for SEO or clarity
- Translate if needed (e.g., Spanish → English)
Integrate into the website or code
- Paste into CMS fields
- Insert into templates
- Use in code comments, config, or documentation

This workflow is what allowed me to finish that May 15th project comfortably before the deadline.

When not to blindly trust OCR

For students, office workers, digital marketers, and copywriters, here’s what I don’t recommend fully automating:

Financial documents
Invoices, receipts, contracts with fees, salary details.
→ Use OCR to speed up, but double-check all amounts.
Legal or compliance text
Contracts, terms and conditions, policies.
→ OCR can extract, but you must verify exact wording.
Critical dates and codes
Expiry dates, coupon codes, license keys, product batch numbers.
→ Verify manually; OCR can easily misread individual characters.

Use image-to-text as a fast first draft, not a final authority, for anything where tiny mistakes can have big consequences.

How to get better OCR results (simple, practical tips)

No deep tech knowledge needed. These alone improve your accuracy a lot:

Use clear screenshots instead of photos when you can
- Screenshots are usually sharp and flat.
- Avoids blur, perspective problems, and shadows.
Crop to the actual text area
- Don’t include toolbars, sidebars, or decorations.
- The cleaner the input, the cleaner the output.
Prioritize readable fonts
- If you’re designing something that you’ll later OCR (e.g., your own PDFs), avoid overly decorative fonts for key info.
Always review numbers
- Dates, prices, years, quantities, IDs.
- This is where small errors matter most.
For big jobs, consider paid plans
- Free tools are good for experimenting.
- If you’re working with dozens of images and tight deadlines, the time lost to captchas and ads can cost more than a small weekly Pro plan.

So, can we really convert image to text?

Based on my day-to-day work as a developer and content manager:

Yes, we can reliably convert images to text for most practical use cases:
- Website copy from PDFs and books
- Notes and handwritten ideas
- Social media screenshots
- Code snippets
- Reference material for copywriting
Yes, but beware when:
- Fonts are fancy or distorted
- Images are low quality
- Numbers and dates matter a lot
No, don’t trust it blindly for:
- Critical financial data
- Legal text where every word matters
- Cases where a single character error is a serious problem

Used with a bit of common sense, OCR and image-to-text converters can:

Turn hours of typing into minutes of checking and editing
Help you meet deadlines
Let you work across languages (like Spanish → English)
Free your brain from boring manual work, so you can focus on actual thinking and creativity