Image Enhancement TRIZ Cases

A 3D ray-and-solid-angle approach quantifies camera-LiDAR parallax, guiding sensor placement to improve fusion and object detection.

Roadside streetlight modules detect hazards beyond vehicle line of sight and relay alerts to nearby vehicles and neighboring lights.

Static point cloud processing with LIDAR, IMU, GNSS, and cameras enables real-time railway wire height, stagger, and gauge measurement.

Compressed RADAR point clouds, tile deltas, and pose data cut transmission load while preserving map accuracy for autonomous localization.

Weighted fusion of multiple camera and sensor pose estimates improves 3D map stability and obstacle detection under vehicle and object motion.

Gas pouch expansion during cell formation is converted into volume data to score battery quality without destructive SEI testing or long inventory holds.

Motion data from an event camera triggers image capture only when needed, cutting vehicle vision processing and communication load.

Multi-sensor checks and ICP verify whether an autonomous vehicle moved during a power cycle, enabling fast, high-confidence re-localization.

Fused upper and lower camera views use tire-pressure-based transparency to reveal boom-blocked forward sight in construction machinery.

Camera-based child seat recognition uses 3D reference models, AR displays, and audio cues to improve mounting accuracy without added hardware.

Temperature control shifts substrate alignment symbols through thermal expansion to correct overlay errors before semiconductor lamination.

A checkerboard-based multi-camera calibration approach cuts manual setup and improves image splicing accuracy in vehicle panoramic systems.

Few-shot image translation generates synthetic trailer views to retrain in-vehicle AI when unfamiliar trailer angles cannot be detected.

Rotationally symmetric grating pairs create larger-pitch Moiré patterns that reduce noise and improve semiconductor overlay error measurement.

Multi-level analysis of image features and vehicle dynamics detects camera misalignment root causes and supports safe vehicle control.

Low-light selenium imaging and a global shutter improve collision prediction, enabling airbags to deploy before impact, including side collisions.

An integrated road line and adaptive ROI help vehicle controllers judge object motion despite sensor errors, reducing unnecessary deceleration.

Pet tracking with imaging and RF signals lets a vehicle disable or modify nearby controls to prevent accidental pet-triggered inputs.

Beam profiling and image-based defect detection identify mask damage before laser annealing, improving irradiation accuracy and substrate yield.

Optical geometry capture plus X-ray edge spacing checks verify battery layer alignment, cutting overdimensioning, material waste, and stack weight.

LiDAR-camera fusion labels obstacles by collidability, reducing vegetation misclassification, over-braking, and rear-end risk.

Vehicle image and odometry data generate 3D lane-feature labels automatically, cutting curation effort while improving trajectory prediction.

Template matching within divided wafer image regions locates alignment marks accurately across changing viewing conditions without template re-registration.

Weighted basis functions isolate logic-structure scatter from stacked memory signals, cutting fitting error and computation time.

Voltage-contrast SEM inspection reveals shorts between conductive lines by flagging unexpectedly bright transistor contacts after pre-charge.

Planar homography segmentation from sequential vehicle camera images enables real-time object detection across nearly the full scene.

By comparing tracked objects with the driver's field of view, this case cuts AEB false triggers while preserving timely alerts.

By selecting the best frame and prioritizing critical signs, this case cuts controller load while improving in-motion sign recognition.

Stereo camera depth overlays add terrain distance cues to remote construction vehicle video feeds, improving control and reducing damage risk.

Driver-set no-entry areas on a bird's-eye vehicle view let the controller reroute and stop safely without crossing prohibited zones.

Vehicle image sensors estimate road slipperiness to flag high-risk areas and trigger warnings or speed adjustment in bad weather.

Optical, ultrasonic, and weight-based FOUP inspection detects damage and contamination without opening the container.

Sparse LiDAR points are projected onto image pixels to infer dense depth, improving vehicle object detection and trajectory planning.

Sensor-driven display and haptic adjustments align in-cabin visuals with vehicle motion to reduce passenger motion sickness.

Real-time analysis of inspection data adjusts node-specific parameters to improve defect detection accuracy and reduce repeat measurements.

A diffusing panel and segmented eyebox capture multiple HUD calibration patterns at once, cutting end-of-line calibration time.

Rear camera image points and trailer edge geometry are used to calculate trailer angle accurately without extra hardware sensors.

Judging ceramic electrode degradation enables cleaning, heat treatment, and reassembly to restore lithium-ion battery performance at lower recycling cost.

Automatic waveform timing, confidence thresholds, and gain control keep front ultrasonic sensing active while reducing vehicle-to-vehicle interference.

Boron-containing SEI formation and black unevenness index control reduce central electrode heat generation in high-capacity Li-ion batteries.

Image processing uses positioning holes to detect anode composite strip offset and angle faster and more precisely than manual inspection.

Alternating NIR-bright and dark seatbelt stripes let cameras verify proper belt positioning and occupant distance beyond buckle switches.

Image brightness analysis detects oncoming vehicle lights at night and triggers alerts to help drivers react sooner and avoid accidents.

LiDAR point clouds and movable body keypoints enable accurate human pose annotation in low light while preserving 3D depth context.

Multi-camera robot guidance detects wire contacts and connector holes to align wire ends for faster, more flexible automated insertion.

Interpolating image parameters in overlapping camera regions removes brightness steps and improves 3D vehicle surround view quality.

Image comparison detects wheel nut rotation against a stored reference, avoiding sensor wiring while simplifying looseness checks.

Selective sensor and landmark algorithm activation cuts energy and computing load while maintaining vehicle localization in parking infrastructure.

Multiple cameras and object sensors reconstruct pillar-blocked views, track hazards, and warn drivers earlier to reduce collision risk.