🧾 OCR Receipt Scanner

About OCR Receipt

A receipt is a small document with a predictable shape: date at the top, vendor name, line items, total at the bottom. This tool reads that shape and pulls the key fields into text you can copy into a spreadsheet or expense report, instead of typing them from a photo.

The shoebox problem

Everyone who has ever claimed expenses knows the shoebox. Receipts from taxis, coffees, client lunches, office supplies, the printer ink you bought at 11pm because the big presentation was tomorrow, they pile up in pockets, wallets, glove compartments, and eventually a drawer you avoid opening. At tax time or when a client asks for a detailed invoice trail, that shoebox becomes a weekend-destroying typing exercise.

Each receipt has to be opened flat, squinted at under bad light, and its date, vendor, and total transcribed into a spreadsheet cell. Multiply that by a year of ordinary spending and you are looking at hours of work that produces nothing but a list you could have had in January if the paper had just become data on the spot.

What the extractor is actually looking for

Receipts are not designed to be read by machines. They are designed to be read by hurried customers at a counter, and they show it. The date might be printed in a dozen formats (03/14, 14.03.2024, March 14 2024) often in the same receipt. The vendor name might be a stylised logo at the top, a legal entity name at the bottom, or both, and they rarely match what you would type into an expense claim.

The total is usually the largest number on the page, but not always; a subtotal, a tax line, and a change-due line can all look similar in monospaced thermal print. This tool is tuned for that structure. It hunts for the date field wherever the format allows, identifies the shop or merchant name near the top or in the header area, and isolates the final total from the noise of line items and tax breakdowns. What comes out is not a dump of every character on the page, it is the handful of fields you actually need to file the expense.

The parts of receipts that usually break other extractors

Generic OCR is easily confused by receipts. Thermal paper fades unevenly, so the left edge might be crisp while the right edge dissolves into grey. Logos and decorative borders inject shapes that a less specialised recogniser tries to interpret as characters. Discount lines, loyalty point balances, and payment method footers crowd the bottom third with numbers that look like totals.

Cash receipts introduce another wrinkle: the "cash tendered" and "change" fields are amounts too, and a tool that simply grabs the last number on the page will often return your change instead of what you spent. The receipt-specific logic here filters for the structure rather than the last number, and it tolerates the visual noise that would derail a general-purpose image-to-text pass. Extremely faded or badly crumpled paper will still challenge it (no recogniser reads what is physically gone) but ordinary wear and tear is handled.

From a pile of paper to a spreadsheet you can file

The workflow is deliberately short. Photograph each receipt, upload the images, let the extractor pull the fields, and review what it found before exporting. Review matters: a faded 6 might read as an 8, and the cost of catching that at review time is a second; the cost of catching it during an audit is a corrected filing months later.

Export goes to CSV for spreadsheet software or to PDF if you need a single document that pairs the data with the receipts themselves. Whether you are reconciling a month of freelance expenses, preparing a tax claim, or just trying to keep personal spending honest, the point is the same: the paper stops being the record and becomes the receipt for the record, the data lives where you can sort, filter, and total it.