ConductVision Enterprise

Optical Character Recognition

Extract text from containers, signs, labels, and serial numbers in more than 40 languages. Available for pilot.

Example optical character recognition scene with an illustrative detection overlay
Illustrative detection overlay, drawn for demonstration. Not model output.

Optical Character Recognition reads printed and stenciled text from physical objects captured in video streams or images. The system handles ISO 6346 container codes, warehouse labels, serial numbers on equipment, safety signage, and multilingual text across 40+ languages. Unlike document-focused OCR tools, this system is purpose-built for industrial and field environments where text appears on curved surfaces, under uneven lighting, and at oblique angles. Results are structured and searchable, designed to feed directly into inventory, logistics, and compliance systems.

How it works

Optical Character Recognition in three steps

Connect

Position Cameras at Read Points

Mount cameras at container yards, conveyor belts, loading docks, or facility entrances where text needs to be captured. The system calibrates for distance, angle, and expected text regions automatically.

Analyze

Detect and Extract Text

A text-detection model localizes text regions in each frame, then a recognition model decodes characters with language-specific dictionaries. Post-processing validates against expected formats like ISO 6346 container codes.

Act

Structure and Deliver Results

Extracted text is parsed into structured fields (container number, check digit, owner code) and delivered to downstream systems via API. Misreads are flagged by confidence score for manual review.

Features

ISO 6346 Container Code Reading

Reads and validates intermodal container codes including owner code, equipment category, serial number, and check digit. Validates check digits automatically to catch misreads.

Serial Number Extraction

Reads serial numbers, part numbers, and asset tags from equipment, packaging, and components. Handles embossed, stamped, and printed text on metal, plastic, and cardboard surfaces.

Multi-Language Support

Recognizes text in 40+ languages including Latin, Cyrillic, Arabic, Chinese, Japanese, and Korean scripts. Language detection is automatic or can be specified per camera.

Safety Sign and Label Reading

Captures text from safety signs, hazmat placards, and regulatory labels. Useful for compliance verification and automated inventory of posted signage.

Curved and Angled Surface OCR

Perspective correction and dewarping algorithms handle text on cylindrical containers, angled signs, and surfaces viewed at up to 60 degrees from perpendicular.

Batch Image Processing

Upload folders of images for offline text extraction. Results are returned as structured JSON or CSV with image filename, detected text regions, and confidence scores.

Use cases

Container Yard Automation

Shipping terminals process thousands of containers daily and need accurate code reads for tracking. Automated ISO 6346 reading can replace manual data entry at gate lanes and crane operations.

logisticsshipping

Warehouse Inventory Verification

Warehouses need to verify that the right products are in the right locations. Camera-based label reading at dock doors and aisle intersections can catch mis-shipments before they propagate.

logisticsmanufacturingretail

Manufacturing Quality Control

Production lines print lot numbers, date codes, and serial numbers on products. OCR can verify that printed information matches the production order, flagging discrepancies in real time.

manufacturingpharma

Utility Asset Management

Utility companies maintain thousands of poles, meters, and transformers with stamped serial numbers. Mobile and drone-mounted cameras can read asset IDs during inspections, eliminating manual transcription.

utilitiesenergy

Hazmat Placard Identification

Emergency responders and facility managers need to identify hazardous materials quickly. Automated placard reading can extract UN numbers and hazard classes from truck and container signage.

logisticsgovernmentemergency services

Technical overview

Models
CRAFT text detector + TrOCR-based recognition with language-specific fine-tuning
Input formats
RTSP, ONVIF, MP4, JPEG, PNG, TIFF batch
Output formats
JSON (structured fields), CSV, XML, Webhooks
Edge support
NVIDIA Jetson, Intel NUC, portable ruggedized units for field use

Accuracy and latency are measured against your footage and cameras during pilot scoping; we publish figures only with the conditions they were measured under.

Evaluate Optical Character Recognition on your footage

One prioritized outcome, your cameras, a structured results review.