Image Enhancement TRIZ Cases

Dual focal-length imaging improves EV battery swap positioning and lock-state checks, cutting manual adjustment and replacement time.

Sensors and predictive control let a trailer adjust tilt, dimensions, and surfaces to match user profiles and selected activities.

Surfel maps and textured rendering generate realistic simulated sensor data at scale, reducing manual scene creation for autonomous vehicle training.

Low-speed vehicle localization is stabilized by weighting odometry over lane recognition to reduce lateral position errors and false control actions.

Sensor fusion compares camera and radar or lidar distances to detect camera drift and automatically correct external parameters for stable vehicle ranging.

When rain, snow, or dust blocks the windshield, sensors trigger a transparent display that renders a real-time GAN reconstruction of the road scene.

Uses image feature matching against selected sparse 3D map sub-volumes to localize vehicles in GPS-denied areas such as parking garages.

Rear camera edge detection estimates trailer hitch angle without laser calibration and stays usable across different drawbar shapes.

Video-based monitoring tracks bonding wave propagation during wafer bonding to detect defects early, reduce scrap, and improve yield.

A camera and processor estimate obstacle height from a 2D image using a projected reference line, avoiding costly LiDAR and extra deep learning.

Neural-network object recognition and time-to-collision control help personal mobility devices warn riders or brake before impact.

Adaptive sampling rates focus point cloud detail on specified objects, improving autonomous navigation accuracy while reducing processing load and map storage.

Multiple circular-target images at different polar angles extract axis edge widths to reconstruct electron beam spot shape accurately.

Onboard camera analysis estimates passenger height from body features, helping airbags and seatbelts adapt to children and adults.

Separating moving-object and distant-scene feature points improves image-based object position and motion recognition accuracy.

Camera-based body keypoint analysis estimates occupant height and age to adapt airbag and seatbelt control for children and adults.

Image segmentation and movement vectors help microscopes keep target objects in view despite noise, improving 3D and time-series tracking.

Sensor data identifies vehicle events first, so only matching dashcam video is uploaded, cutting processing load and communication cost.

A dynamic projection matrix blends vehicle and trailer camera feeds by trailer angle to remove blind spots during turning and sway.

Headlight and taillight recognition reveals adjacent vehicle orientation faster than steering-wheel detection, improving perpendicular parking accuracy.

Image analysis detects personnel, patient equipment, and temperature to automate ambulance access and cabin condition control.

Camera and LIDAR fusion improves lane marking continuity and accuracy across long distances and adverse road conditions.

Crowdsourced sparse maps use road-feature lines and landmarks to guide autonomous vehicles while cutting map storage and transfer load.

Correlating in-soil sensors, imaging, and activity data at one location enables proactive crop decisions from local soil and growth conditions.

A color-camera metrology approach maps substrate pixels in color space to track layer thickness and improve CMP endpoint control.

Alternating vehicle lights and camera reflections estimate coupler depth, enabling faster, more accurate trailer hitch alignment.

Wheel and lane segmentation maps reduce 2D perspective distortion, improving vehicle-to-lane distance and pose estimation.

Integrated sensors, fiducial markers, and mobile alerts help verify child presence, buckle status, and correct car seat positioning.

Dual-lens imaging and neural recognition track photoresist spray patterns in real time to cut resist waste and reduce false alarms.

Segmented semiconductor regions with graded impurity levels suppress SPAD noise while preserving avalanche gain and signal accuracy.

Multiple detector views and AI defect recognition guide e-beam reticle repair to avoid over-etching and reduce manual error.

Sensors, profiles, and predictive control let a trailer adjust tilt, surfaces, and dimensions for different activities and users.

Camera-based lane centering uses lane quality thresholds and rate-limited width updates to stay stable when road markings fade.

A rear camera estimates user height from segmented images to set tailgate opening angle automatically, avoiding repeated manual adjustment.

Optical path compensation and reflected light let one camera inspect pouch battery tape across upper, side, and lower surfaces accurately.

An addressable VCSEL crossed-line projector shrinks structured-light depth sensing while preserving spatial resolution for lightweight headsets.

Phase-based eye depth mapping improves gaze accuracy without heavy 3D rendering, enabling real-time optical refocusing for VR and AR.

Camera-based gaze sensing detects amblyopia or strabismus and adjusts warning brightness, position, or timing for safer hazard alerts.

Segmented upper-side light shielding blocks sunlight and lamp glare while preserving wide-angle vehicle imaging and distortion correction.

An end-to-end lidar model predicts object trajectories directly from 3D point clouds, cutting tracking-stage errors and redundant frame processing.

Dynamic warning regions use side images, radar, speed, and turning angle to cut false blind spot alerts while keeping close-object warnings.

Lane count and driving direction are used to place vehicle AR eco-state displays accurately when precise maps or positioning are unavailable.

CNN video detection combined with V2V blind-spot status sharing maintains warning accuracy when GPS degrades or cameras face low light and contamination.

Planned self-position data reshapes the bird's-eye projection surface ahead of vehicle motion to avoid lag and unnatural surround images.

Fusing wheel speed, acceleration, GPS, and camera data improves true vehicle speed estimation for ABS and traction control on low-friction roads.

FOE, lane width, and ground-level changes help a monocular vehicle camera distinguish real roads from wall drawings and avoid collisions.

Homography-based plane motion from sequential monocular camera images improves dynamic object detection near the epipole in real time.

A transparent mounting surface and shims reveal sealant compression and gaps in rearview mirror attachment testing, helping pinpoint leak causes.

A slice loss function flags LiDAR depth outliers from glass-induced vehicle slicing, improving depth maps for safer vehicle control.

When parking lines are hard to detect, virtual parking spaces are generated from panoramic images and nearby vehicles to enable automatic parking.