Image Analysis TRIZ Cases

Two-stage light scanning narrows object search from standard regions to basic regions, cutting computational load and input delay in AR and XR.

A tagged serialized MR step hierarchy replaces manual porting, preserving procedure structure across platforms with less time and resource use.

Local-to-global PRNU variability comparison uses F-statistics to detect digital image tampering with high precision and lower processing load.

3D imaging is correlated with RF coverage maps to locate indoor user devices precisely without extra beacons or specialized GPS hardware.

Independent bounding-box adjustment across multiple camera views speeds projector boundary alignment and removes discontinuous stitched edges.

User-combined media is duplicate-checked before minting on-chain assets, expanding presentation styles while reducing wasted virtual resources.

Touch-adjustable measurement overlays let users reposition ultrasound measuring points accurately without obscuring the underlying image.

Classifying basic and additional views enables decoder-side depth estimation, reducing immersive video redundancy while supporting 6DoF rendering.

Automatic target highlighting and trigger-based non-contact control make virtual object interaction more immersive without complex gameplay.

Electric symbols are grouped into shape families, then clustered from neural features to improve construction drawing extraction and counting accuracy.

Controlled illumination and distance scanning capture surface appearance changes to verify holograms and original photos in identity documents.

Image processing identifies existing orthopedic implants and reconstructs pre-implant joint anatomy for more accurate revision surgery planning.

Satisfaction-level prediction lets video sources auto-tune image parameters across changing scenes and camera models without manual calibration.

A controllable hot mirror array redirects infrared eye reflections to the camera while preserving view-through optics in compact head-mounted displays.

Spectral CT isolates contrast attenuation along a vascular lumen to calculate gradients more accurately for blood flow assessment and FFR.

A spatial alignment image and timestamped offset calculation let two AR devices align disjoint coordinate spaces for consistent shared imagery.

Surface temperature change analysis distinguishes real faces from 3D masks faster and with less subject discomfort.

Predefined offset indices simplify affine motion prediction, improving video compression while limiting coding complexity and encoding time.

Contactless imaging maps multiple pipette tip orifices against a virtual grid to catch misalignment before high-throughput pipetting starts.

Patient-specific B1 projection data enables MRI shimming in about one second, improving RF field uniformity and reducing dielectric artifacts.

Timestamp-based event frames capture movement changes from sparse event data, improving optical flow speed and accuracy.

Machine learning predicts geological features from incomplete sketches, preserving intuitive drawing while improving digital consistency and accuracy.

Semantic maps and motion limits let XR overlays move in real time while blocking display in restricted or hazardous locations.

By separating identity and texture from facial features across video frames, this case improves expression coefficient accuracy for speaker and expression analysis.

Automated trap imaging crops the collection chamber to count grain-storage insects in real time, cutting inspection delay and labor.

Camera feedback captures overlapping projected images, identifies absolute shift direction, and corrects tiled image misalignment.

Uses a perspective camera and PLIKS solver to reconstruct accurate 3D human meshes from one image with better alignment and depth realism.

Multiple TDI imagers scan tissue continuously and in parallel, cutting imaging time while preserving high-resolution fluorophore separation.

SR content events are timed to audio and matched to the user environment, creating a more immersive playback experience with less continuous processing.

Reference lines and grayscale-ratio points locate a camera optical center accurately while avoiding full-pixel image processing.

Height-corrected sound localization helps cameras avoid reflection errors and keep focus on the actual active talker.

Adjusting displayed training image size with camera distance keeps lensless blur consistent, improving model accuracy while preserving privacy.

A dual-controller camera tracking scheme uses angle-of-view shifting for small motion and pan-tilt drive only when needed to keep subjects centered.

Frame-level image hashes improve illegal image detection despite pixel changes while preserving privacy by avoiding image content analysis.

Semantic segmentation and rotating object detection identify forbidden-region violations despite camera angle changes and background noise.

A conical optical element overlaps reflected light from both eyes on one sensor, simplifying fixation inspection while reducing size and alignment burden.

A movable marker changes position and orientation to stay visible for optical tracking during 3D medical imaging despite patient or instrument blockage.

Automatic per-region calibration uses horizontal and vertical plane fitting to improve monocular depth accuracy without manual setup.

Adjusts overlay frame size to a detected person's height and distance, reducing position misreading for shorter individuals.

Dual-threshold visual signature updates with user validation help track individuals across cameras despite viewpoint and posture changes.

Balances marker visibility and image quality against radiation dose by adjusting x-ray source, detector, and collimator settings.

Real-time camera and sensor feedback identifies when a microtome is cutting only embedding material, reducing trimming errors and tissue loss.

Object and voice recognition place spoken text directly on the relevant image area, cutting memo steps and matching user intent.

Distributed edge intelligence and service chains keep ambient clinical documentation running during network loss while reducing bandwidth use.

Grid-level ROI prediction replaces heavy category scoring to cut memory and time while producing finer instance segmentation masks.

Rendered logo detection combined with source verification helps catch phishing pages and emails even when code is obfuscated.

An AR model aligned with GNSS, EDM, and surface coordinates helps measure buried asset depth accurately despite changing ground levels.

Using only two perpendicular DR images, a trained reconstruction model speeds 3D CT imaging while preserving image quality.

Weighted vertex areas shift the centroid in triangle voxelization to cut rendering distortion while preserving point cloud compression efficiency.

Bounding-box and boundary checks keep 2D mesh patches overlap-free, improving 3D compression efficiency while limiting extra processing.