Image Analysis TRIZ Cases

A stereo camera adjusts interaxial distance and zero-parallax plane depth to capture stereoscopic images.

An optical detection system calculates relative speaker position and angle to eliminate manual technician calibration.

A guidelines segmentation system generates snapping references from object edges to align text and objects with raster images.

A 3D preview system displays virtual objects within an application environment using interactive affordances and visual indicators.

A control system computes multiple saliency features and generates a spatial weight map to adjust image segments for accurate main subject extraction.

Glasses adjust lens diopters via positioning and visual acuity mapping to eliminate eye strain from switching between near and far viewing distances.

A row decoder and digital logic circuit use a power switch to isolate supply voltage during idle periods, reducing leakage current in image sensors.

A mobile device captures biometric data during user input to verify identity and switch states automatically.

Convex polygons represent navigable areas in indoor map models to enable efficient route-finding operations on mobile devices.

A 3D measurement device adjusts exposure time based on target reflectivity to maintain sufficient feature points.

Patch-based reshaping reduces banding artifacts in 3D video point clouds while maintaining accurate reconstruction across devices.

An authorization code bridges mobile devices and carrier billing systems to enable electronic shipping payments.

A parametric image selection method assigns energy values to pixels based on distance and color differences to generate precise digital data masks.

Segmented dual interface system reduces developer skill requirements by switching between point-and-click and scripting views for vision inspection programming.

Segmenting image processing into specific regions reduces computational complexity and time while maintaining detection accuracy.

An image processing system automatically associates tracking devices with tracked assets using visual identification, reducing manual input errors.

A moving image generation apparatus calculates goodness-of-fit indices for captured 3D model images to determine optimal virtual camera parameters.

Intensity-based filtering reduces excessive data processing time by selecting significant feature points for robust image matching.

Structured infrared dot maps with replicated sub-patterns improve depth accuracy on smooth surfaces while reducing computational burden.

A gradient-based edge detection method identifies mini-vectors to trace object boundaries with single-pixel precision.

A contact angle measurement method corrects apparent angles using surface inclination data from captured images.

Dynamic pattern light irradiation enhances parallax value accuracy by mitigating image abnormalities like shadows and reflections.

An AI model infers image editing operations from natural language requests, automating localized adjustments that reduce manual effort and time.

An image processing device extracts contour directions and apex boundaries to identify the principal face of an object.

A sensor device detects occupant movements using infrared or radar circuits to generate distinct signal patterns for entry and exit tracking.

Top-view imaging identifies foam distribution on liquid surfaces, preventing contamination during automated pipetting operations.

A computer processor compares 3D model characteristics against a domain-specific database to identify object variations.

A wearable device scans assembly stations to display component positions directly to operators.

A projector lens distortion correction method using nonlinear line analysis to calculate accurate 3D coordinates.

A verification system issues motion and audio challenges to capture multi-modal user responses for automated liveness detection.

A virtual environment system fills voxel blocks within a target 3D model contour to construct objects.

Segmenting detection into circular feature figures and surrounding feature points resolves the contradiction between method simplicity and recognition accuracy.

An on-board recognition apparatus estimates road surface area to judge feature point reliability for accurate obstacle detection.

Dynamic basis vectors replace fixed parameters to resolve accuracy limits in complex human motion generation.

A logo recognition system uses specialized text, image, and sign modules to identify logos in images.

Marking changed bitmap objects reduces network data transmission and processing resources during animation frame updates.

Computer process generates tagged training images with simulated printing errors to train machine learning systems.

A video processing system identifies valid edge center pixels and determines symmetry values to classify test regions of interest.

RANSAC-based triangle detection analyzes line segments to identify geometric compositions, resolving accuracy complexity tradeoffs.

A dual-resolution detection device identifies road mirrors and reflections using low-resolution data before extracting high-resolution partial images for precise object localization.

External processor extracts failure video images from real-time endoscope streams using trigger signals.

Exterior tags visible through vehicle windows enable automated interior sensor calibration, eliminating manual tag placement and reducing assembly time.

Associating preview posture data with recorded panoramic video eliminates manual viewing angle adjustment during playback.

A face detection system segments facial features into specialized classifiers to identify specific expressions like smiles and blinks.

Automated privacy preservation system dynamically sanitizes image data based on spatial position and orientation.

An image search system acquires color specifying information and reference data to identify target images based on specified proportions.

An adaptive system classifies spaces by structure to select images for natural 3D texturing.

An image acquisition apparatus captures test images at varying focal lengths to detect optical distortion through line width measurements.

An image recognition apparatus adjusts the event data reference period based on target object metadata to optimize processing.