Image Enhancement TRIZ Cases

A video analyzer generates cumulative distribution function curves to measure signal luminance and identify dynamic range features in real time.

A learning data generating apparatus maps precise map shape information to camera images for automated training data creation.

Automated neural networks segment amniotic fluid regions despite fetal limb movement, improving measurement precision and processing speed.

Image processing device identifies moving regions to extract stationary object features from non-overlapping areas.

Combining RGB and depth data resolves segmentation inaccuracies for transparent elements in video conferencing.

A microscope image analysis method selects optimal focal planes to streamline depth scanning across multiple spatial regions.

Laser ablation forms a straight slot through the gate to deposit metallic solution, repairing bubble-induced open-circuits while preventing short-circuits.

Image processing identifies runway position and centerline to enable autonomous landing without instrument landing systems or GPS.

Segmenting images into areas allows a pre-trained model to refine boundary points, resolving accuracy issues from varying lighting conditions.

Processor compares current and stored landscape images to select the clearest view, bypassing cloud or darkness obstructions.

Depth adaptive hierarchical hole-filling reduces geometric distortions and noise by processing depth maps across multiple resolution levels.

Modeling transition region color differences with a logistic function reduces calculation costs and eliminates chromatic aberration artifacts.

Projecting virtual model markers onto objects automates camera alignment, eliminating complex manual calibration steps.

An AI system validates rapid test results by capturing images and analyzing device alignment with machine learning models.

Backend servers analyze vehicle images to identify static landmarks, reducing onboard sensor complexity and cost.

Tilt reduction aligns tissue layers in tomographic images, maintaining model accuracy without retraining.

A virtual camera system applies nonlinear transformations to subimage data for assembling bird's eye views.

Wavelet subband segmentation with adaptive thresholding reduces noise and flicker while preserving sharp transitions and temporal information.

A convolutional neural network processes T2-weighted and ADC MRI data to segment prostate lesions.

Embedding timestamps in rolling shutter scan lines resolves temporal misalignment between image and LIDAR sensors, improving object detection accuracy.

Orientation sensors validate homography decomposition by comparing measured yaw, pitch, and roll angles against derived rotation matrices.

An image processing apparatus rearranges overlapping images by in-focus position to extract focused areas for depth combining.

An AI engine generates confidence scores to identify relevant echocardiogram loops for cardiologist review.

Edge detection determines variable density transparency levels in a foreground layer, preventing background pixels from obscuring text readability.

Machine learning generates 3D models directly from irregular 2D sketches without manual conversion steps.

A method calculates local contrast values using edge occurrence and noise estimation to determine digital image sharpness.

A weighted landmark determination engine merges detection and optical flow data to track facial landmarks.

A depth image upsampling method maps low resolution data into a high resolution color image to reconstruct detailed depth information.

Subdivides high dynamic range pixel data into parallel partitions to enable lossless neural network inferencing without quantization.

A dual AI model system corrects reference annotation errors during training to improve crowd counting predictions.

Medical image processing apparatus acquires multiple defect maps to generate interpolation target maps for detecting defective elements.

Proximal symbol pairs maintain high Hamming distances to reduce pattern misrecognition errors during 3D reconstruction.

Grouped feature segmentation with random attention mechanisms reduces intra-class differences and increases inter-class differences for accurate classification.

AI device captures user gaze and calculates distance to its camera for precise target identification.

Segmenting static and dynamic data resolves complexity trade-offs, enabling accurate classification of abnormal physiologic movements in 4D CT scans.

A neural network generates precise embedding vectors for item features, resolving accuracy limitations in traditional recommendation systems.

Digital apparatus with specialized sensor arrays captures golf club shaft and scoreline images for precise angle calculation.

A defect calculation system corrects image data using reference objects of known dimensions to determine precise structural flaw sizes.

Context codes encode design geometry to classify regions and determine defect criticality, reducing nuisance detections without a priori knowledge.

Unified object boundaries determine interference potential from positional relationships between detected objects.

A method extracts relevant color information from camera images to identify analytes in multiple coloring rounds.

Assigning predetermined vector values to area units resolves slow convergence in stochastic motion estimation.

Detects image features using depth-dependent physical scale to differentiate real objects from miniature models.

A camera parameter calculation apparatus determines calibration settings using pixel values at projected coordinates.

A signal processing device applies selective grayscale amplification to enhance image quality while preserving On-Screen Display uniformity.

Video augmentation creates diverse training samples from few demonstrations, resolving the trade-off between data collection time and recognition reliability.

Preliminary action stores predetermined time differences to adjust reading timing, resolving alignment issues caused by transversely mounted sensors.

A colorcloud generates a 3D virtual representation of color information from video to capture every color and its frequency.

A learning-based discrete cosine transform noise filter processes images through gamma correction and overlapping patch suppression.

Rotating object regions to minimize width resolves precision issues in inclination detection without complex mechanical sensors.

A processing device detects correspondence points using a common wavelength range across multiple images to register them accurately.

Depth-regularized reconstruction using ultrasound segmentation resolves light shadowing and underestimation in diffuse optical tomography.

A structured light depth sensor adjusts scan parameters based on detected object motion.

Reconstructs field of view using sharpness detection to eliminate redundant image data and reduce examination time.

A measurement device calculates object dimensions using depth and color data to display contour frames for user interaction.

Deep learning analyzes chest X-rays to stratify risk before molecular testing, resolving the trade-off between diagnostic accuracy and time.

A multi-label classification model trains on difficulty-based image subsets to generate comprehensive abnormal feature labels.

Assigning region proposal network confidence levels boosts classifier background scores, reducing false positive rates in pedestrian detection.

A mobile device determines its position by scanning visual attributes like shapes or colors with a camera and matching them against a database.

A neural network model processes ultrasonic echo signals through convolution and pooling to extract target features.

A medical imaging apparatus extracts muscle tissue figures from 3D volume data to track voxel positions over time.

Learned queries eliminate region proposals and non-maximal suppression, reducing computational costs while maintaining accuracy with sparse annotations.

Video analytics and chromic patches monitor edge sites, eliminating sensor installation complexity while maintaining reliability.

A medical image segmentation system propagates reference regions using translated points and multi-seed selection.

Likelihood functions assign target IDs and track types to objects across video frames, eliminating manual annotation costs for deep tracking datasets.

Amplitude-frequency models derive motion estimates from consecutive frames to resolve accuracy and speed trade-offs in complex textures.

Image segmentation algorithms isolate foreground subjects from video frames to enable virtual background replacement.

A neural network framework generates segmented maps of three-dimensional environments using multi-view monocular inputs.

Orthogonal disparity decomposition segments stereo images into independent feature spaces to generate composite depth maps.

Brightness-based reflection analysis identifies weather conditions using existing vehicle cameras, eliminating the need for additional sensors or color data.

A method for X-ray security screening converts effective atomic number values to a threshold, applying correction factors to attenuation data.

A magnetic resonance system determines field maps by separating stationary and position-dependent components.

Automated scanner image analysis calculates nozzle dot position misalignment correction values for inkjet printers.

A mobile device captures image frames and three-dimensional data to generate building models using augmented reality icons.

Segmented cameras and LEDs enable 3D foot scanning that resolves the trade-off between measurement precision and device complexity.

A multi-resolution pipeline generates dewarped images using a cylindrical 3D geometric surface model derived from stereo camera disparity maps.

Information processing apparatus issues placement notifications for capturing devices based on area specifications.

An image restoration filter applies tailored amplification factors to frequency components based on optical transfer functions.

A color noise reduction method applies distance and edge weights to correct luminance and chrominance values.

Multi-sensor endoscope array computes three-dimensional coordinates from projected images, enabling precise physical location determination.

Automated parsing pipeline reduces diagnostic time by segmenting volumetric data into labeled anatomical regions before interpretation.

Image registration and noise reduction detect fatigue cracks in civil infrastructure, eliminating complex sensor deployment.

On-the-fly path planning extends routes using 2D CT control points, reducing processing time by avoiding full bronchial tree segmentation.

Algorithmic neighborhood construction eliminates human perception errors in four-ball friction tester measurements.

Multi-resolution pyramid guides feature matching to detect landmark pairs in full-resolution images.

Automated sector identification system reads references to associate components with specific turbine distributors.

A 3D time-of-flight sensor uses a reflective surface to redirect light pulses and detect dynamic objects within an enclosed vehicle cabin.

A camera-based object detection device segments image data into distinct regions of interest to extract target position and size information.

A motion detector tracks ultrasound transducer shifts to correct field of view coordinates during imaging procedures.

A probabilistic tree tracing method generates vessel models using reinforcement learning agents to navigate anatomical landmarks.

A super-resolution-based adaptive bitrate algorithm computes costs to select video representations and upscale lower resolution segments using neural networks.

Medical image processing apparatus calculates chest area motion between respiratory phases to determine disease severity levels.

A cost function propagates sparse depth points using feature sets to generate dense depth maps for extended reality displays.

Resampling dual focal spot projection data to a virtual source point resolves missing data artefacts in axial short scans.