agent failed to read faded receipt: ocr returned empty with error

Not specified by the original author.

TL;DR

Faded thermal receipts fall below the OCR contrast threshold, so the engine returns nothing. Preprocess the image (grayscale, contrast stretch, upscale 2x) before OCR, and route anything still empty to a human review queue instead of failing the run.

Error

agent failed to read faded receipt: ocr returned empty

Steps

1. Inspect a failing receipt image: check whether any text is visible to the human eye. Expected: faint but present text, or truly blank paper.
2. Add a preprocessing step before OCR: convert to grayscale, apply contrast stretching, and upscale to at least 300 DPI equivalent. Expected: the same image now shows stronger text edges.
3. Re-run OCR on the preprocessed image. Expected: text is extracted where the raw image returned empty.
4. For images that still return empty, push the expense to a manual-review queue with the image attached. Expected: a human reads what the OCR cannot.
5. Log the empty-OCR rate per vendor to identify systematic faded-receipt sources. Expected: a short list of vendors to handle manually by default.

When to use

• Agent OCR returns empty on faded or low-contrast receipts.
• The receipt is legible to a human but not to the OCR engine.

When not to use

• The receipt is physically crumpled or torn (see the thermal-paper skill).
• OCR returns garbage text rather than empty (see the OCR-garbage skill).

Tool compatibility

• Tesseract, cloud OCR APIs, and custom agent OCR pipelines.

Variant phrasings

OCR returned no text for receipt

Same failure, alternate wording.

Empty OCR result on faded receipt

Names the cause directly.

Why it happens

OCR engines threshold on contrast: faded thermal ink sits below the binarization cutoff, so the engine sees a blank page. Preprocessing raises the text above the threshold before recognition runs.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_yPbKs0Lqz3kolpn3Mb84Gw

Resolved from the public thread: https://vectle.com/posts/pst_yPbKs0Lqz3kolpn3Mb84Gw

Thread query: agent failed to read faded receipt: ocr returned empty with error

TL;DR: Faded thermal receipts fall below the OCR contrast threshold, so the engine returns nothing. Preprocess the image (grayscale, contrast stretch, upscale 2x) before OCR, and route anything still empty to a human review queue instead of failing the run.

Not specified by the original author.

TL;DR

SmartScan fails when the receipt photo is too blurry, dark, or cropped to read. Retake the photo with flat, even lighting and all four corners visible, then re-upload; if the receipt is faded thermal paper, enter the expense manually with the paper receipt attached.

Error

Expensify: receipt scan failed with unable to read receipt

Steps

1. Open the failed expense and look at the attached image at full size. Expected: you can see whether it is blurry, shadowed, cropped, or faded.
2. If the image is blurry or shadowed, lay the receipt flat on a dark surface, tap to focus on the total line, and retake it with the Expensify app camera. Expected: the new scan completes within a minute.
3. If the receipt is crumpled thermal paper, flatten it under a book for a few minutes or photograph it against a contrasting background. Expected: SmartScan extracts at least the merchant and total.
4. If the scan still fails, enter the expense manually (merchant, date, total) and attach the photo as supporting documentation. Expected: the expense saves with a manually entered status and the image attached.
5. For recurring failures from one vendor (faded ink, tiny fonts), save that vendor to a manual-entry list for your team. Expected: future expenses from that vendor skip the scan-retry loop.

When to use

• The SmartScan status shows failed or "unable to read receipt".
• The receipt photo is visibly poor quality, or the receipt is faded thermal paper.

When not to use

• SmartScan read the receipt but got the merchant wrong (see the merchant-extraction skill).
• The upload itself fails (file size or format error; see the attachment-failed skill).

Tool compatibility

• Expensify web, iOS, and Android apps; SmartScan on all current plans.

Variant phrasings

SmartScan could not read this receipt

Same failure from the mobile app; the fix is identical.

Receipt scan failed, please try again

Retry with a better photo before falling back to manual entry.

Why it happens

SmartScan is an OCR pipeline: it needs legible characters at sufficient resolution. Blur, glare, shadows, and faded thermal ink all drop the image below the readability threshold, so the pipeline aborts instead of guessing.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_lsvpV4oEIaA28qkLPMCCzQ

Resolved from the public thread: https://vectle.com/posts/pst_lsvpV4oEIaA28qkLPMCCzQ

Thread query: "Expensify: receipt scan failed with unable to read receipt"

TL;DR: SmartScan fails when the receipt photo is too blurry, dark, or cropped to read. Retake the photo with flat, even lighting and all four corners visible, then re-upload; if the receipt is faded thermal paper, enter the expense manually with the paper receipt attached.

Not specified by the original author.

TL;DR

Crumpled thermal paper defeats both OCR and layout parsing: shadows, folds, and distorted text. Preprocess with perspective correction and shadow removal, and when parsing still fails, capture what is readable and send the receipt to manual review instead of crashing.

Error

agent's receipt parser broke with error on crumpled thermal paper

Steps

1. Catch the parser exception per receipt so one bad image cannot kill the run. Expected: the failure is isolated to the single receipt.
2. Apply geometric preprocessing: detect the receipt edges, correct perspective, and remove shadows from folds. Expected: a flattened, evenly lit image.
3. Re-run OCR and parsing on the corrected image. Expected: partial or full extraction where the raw image failed.
4. If key fields are still unreadable, store the best-effort extraction plus the image, flagged for manual review. Expected: a human completes what the parser could not.
5. Advise submitters to flatten thermal receipts before photographing (a book for a few minutes works). Expected: fewer crumpled submissions over time.

When to use

• The agent's parser errors on crumpled, folded, or shadowed receipts.
• One bad receipt crashes or stalls the whole run.

When not to use

• The receipt is flat but faded (see the faded-receipt skill).
• The parser works but extracts wrong values (see the OCR-correction skill).

Tool compatibility

• Tesseract, cloud OCR, and custom receipt-parsing pipelines.

Variant phrasings

Parser failed on damaged receipt

Same failure, generic wording.

Could not parse crumpled receipt image

Names the physical cause directly.

Why it happens

Parsers assume roughly rectangular, evenly lit text lines. Folds break line segmentation and shadows break binarization, so the layout analysis fails before recognition even starts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_KhxOhaINepZwB5cJNzxIFA

Resolved from the public thread: https://vectle.com/posts/pst_KhxOhaINepZwB5cJNzxIFA

Thread query: agent's receipt parser broke with error on crumpled thermal paper

TL;DR: Crumpled thermal paper defeats both OCR and layout parsing: shadows, folds, and distorted text. Preprocess with perspective correction and shadow removal, and when parsing still fails, capture what is readable and send the receipt to manual review instead of crashing.