Image Analysis TRIZ Cases

Selective illumination and sensor-data fusion improve low-quality vehicle sensing regions, reducing uncertainty in surroundings models.

Road reference lines and chart images let vehicles verify camera resolution during driving and adjust automated driving levels when quality drops.

Multi-angle imaging detects overlapping battery sheets during conveyor transport, preventing sheet damage and stack-process faults.

A high-rate point camera paired with a lower-rate ID camera cuts processing load while preserving accurate vehicle environment perception.

Multiple camera views detect overlapping battery sheets on a conveyor, enabling alarms or transport stops to prevent defects and equipment damage.

A character replacement schema corrects ambiguous plate reads, enabling accurate vehicle profile lookup and smoother automated service flow.

Parallel road edges and stored feature ratios help estimate the vehicle lane boundary when markings are obscured or absent at intersections.

Coordinates manufacturing messages into defect analysis queues so AI and assisting devices can identify defect type, location, and size faster.

Updates software by processing unit and validates it first in lower-risk vehicles to speed deployment while protecting automated driving safety.

Encoded tree, site, and post-planting image patches are compared to verify that a specific tree was planted in the intended environment.

Roadway protolanes group similar lane segments so autonomous vehicle intent can be tested with less redundancy while preserving geonet coverage.

Detecting the repeat length in stranded wire images keeps segmented inspection regions pattern-aligned and avoids false abnormal judgments.

Laser and image-based inspection checks electrode assembly alignment, miswinding, diameter, and volume without destructive battery teardown.