冀思数据 / Jisi Data
Vehicle Nameplate Verification System
Nameplate photo + OCR vs vehicle master data—auto pass/fail and archiving.
Project overview
Outbound QC: capture nameplate photos, OCR VIN/spec fields, and auto-compare with vehicle master data.
Pass to release and archive; fail to block with retake/manual review—fewer misses and misjudgments.
Multi-model templates support changeovers; photos and judgments remain audit-ready.
Use cases
Capture photo
Station photo with lighting, linked to VIN/model.
OCR parse
Template-based VIN and spec field recognition.
Master compare
Auto pass/fail against vehicle master data.
Recheck & archive
Retake/review on fail; store evidence for audits.
Business architecture
1Photo
2OCR
3Master compare
4Pass/fail
5Retake/review
6Archive
QC station
CameraNameplate photo evidence
QC tabletGuide, retake, judge
Lighting / jigStable capture
VIN entryLink current vehicle
OCR & match
OCR engineVIN and spec fields
Model templatesPer-model regions
Field parseStructured key data
Master compareConsistency check
Decision loop
Pass releaseContinue to next station
Fail blockStop on mismatch
Retake / reviewManual second check
Evidence archivePhotos and results
Plant integrate
Vehicle masterOutbound config baseline
MES / QMSOrder and quality sync
Object storageLong-term images
DashboardsPass rate and issues
Nameplate QC architecture: capture → OCR/match → decision → plant systems.
Highlights
- OCR for VIN and spec fields
- Auto compare with vehicle master data
- Multi-model templates
- Pass/fail judgment & archives