Image Enhancement TRIZ Cases

Automated photo management system identifies unwanted images through quality and interaction analysis.

A ConvLSTM neural network processes spatial data to generate dense depth maps from sparse inputs.

Phase modulation shifts parallel image slices during simultaneous acquisition, reducing scan time and patient discomfort while maintaining measurement accuracy.

A video synthesis device adjusts a virtual projection plane based on detected object positions to create natural images.

Automated deep learning model identifies dendrite structures across full view fields in metal materials.

Deformation fields adjust displacement vectors in a pre-generated movement model to correct for patient positioning errors during radiation therapy.

An image processing apparatus selects optimal feature lines using gradient information to calculate deviation amounts between projected segments and detected edges.

A focusing control device selects filter processing based on subject conditions to enhance phase difference detection accuracy.

A selection unit identifies target regions with minimal difference across time-series images to perform precise average processing.

Simultaneous super-resolution and demosaicing preserves subpixel displacement information lost in conventional methods, improving spatial resolution.

Image sensors in an electronic home plate detect ball motion to resolve human umpire error and improve strike zone accuracy.

A camera-based keyboard system detects keystrokes by tracking fingertip positions on physical keys using mobile device image processing.

An AI system analyzes visual portfolios to rank candidates, replacing manual cataloging and reducing recruitment time.

A computing platform extracts vehicle speed from video footage by detecting brightness transitions across known road markings.

A recalibration process corrects monochromatic image energy levels using petrous bone mass attenuation coefficients.

Light engine projects patterns via adjustable lenses and reticle tray to expand field of view, eliminating ghost imaging that degrades measurement precision.

A dual-energy X-ray imaging system segments abdominal tissue to calculate visceral fat mass from subcutaneous profiles.

An ultrasonic diagnostic apparatus transmits beams in multiple directions to generate tomographic images for quantitative tissue characterization.

A 4D GIS system predicts moving target trajectories using fuzzy logic and Extended Kalman Filters.

A monocular camera system estimates time to collision using ground plane geometry and Kalman filters.

A photomask inspection method averages images from multiple chip regions to generate a standard reference image for defect detection.

Local homography matrices derived from segmentation masks align images across varying planes, resolving plane parallax errors inherent in global models.

Iterative spatial pattern segmentation reduces tissue scattering diffusion, enabling accurate target detection at varying depths.

A coded tracking system adjusts locator emission patterns to resolve individual light sources in captured images.

Calculating average character color removes non-character hues via outlier rejection, resolving background confusion in license plate recognition.

Replacing rotating mechanical components with fixed prisms and beam splitters, the system eliminates human vision dependency for accurate range data.

Minimizing graph energy penalizes value disparities and medial element distances to denoise 3D signals while preserving sharp features.

Classified truncation compensation adapts algorithms to specific body regions, resolving accuracy losses from truncated MR fields of view.

An image processing device extracts and evaluates medical image data combinations to streamline clinical workflows.

An MRI apparatus optimizes imaging parameters to generate stable quantitative value maps.

A package dimensioner detects pose changes using background modeling and depth map comparison to trigger re-initialization.

Automated parameter optimization streamlines image processing setup for machine tool monitoring.

Computer processor generates wafer design to image coordinate mapping through algorithmic pattern matching.

Synthetic range and intensity images from 3D models improve target recognition accuracy despite sensor noise.

A method generates high-resolution images from low-resolution inputs using regression functions trained on local ternary pattern signatures.

A display driver generates pixel-specific characterization data by filtering area features to enable localized contrast correction.

Automated imaging captures exposed layer geometries to drive a ply cutting system, eliminating manual tracing errors and ensuring precise patch fitment.

A learned model generates energy-subtraction images from multiple radiation energies.

A neural network reconstructs chrominance channels guided by de-noised luminance data to produce high-quality primary-color images.

Multi-camera image processing calculates three-dimensional instrument positions without fixed reference points, resolving tracking precision constraints.

A false contour detection method using gradient and simplicity metrics to identify artifacts in video pixels.

A defect identifying method normalizes captured image luminance to enable accurate surface anomaly detection using a single imaging unit.

A fingerprint sensing system captures impairment data to suppress capacitive noise during feature extraction.

Rotationally symmetric Moiré patterns amplify overlay errors through fringe shifts, resolving sensitivity and robustness trade-offs in shrinking design rules.

A system overlays adjusted geometric models onto X-ray images to enhance internal structure visibility.

A photographing apparatus calculates minimum shots and unit exposure times to generate added images with optimized signal accumulation.

A photon counter detector segments X-ray energy spectra into discrete windows to enable precise material discrimination in CT imaging.

A recognition system defines actor inputs and extracts salient features to build a reusable identification model.

Combining fixed and moving camera streams resolves the contradiction between wide coverage and detailed attribute recognition accuracy.