Namespace VisioForge.Core.MediaBlocks.OpenCV

Classes

CVDewarpBlock

OpenCV dewarp block for geometric distortion correction in video streams. This block performs lens distortion correction, perspective transformation, and barrel/pincushion distortion removal using OpenCV's computer vision algorithms. Essential for correcting footage from wide-angle lenses, fisheye cameras, or action cameras that produce geometric distortions. Supports various distortion models including radial and tangential distortion correction. Commonly used in surveillance systems, automotive applications, and 360-degree video processing. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVDilateBlock

OpenCV dilate block for morphological image processing operations. This block performs dilation, a fundamental morphological operation that expands white regions (foreground objects) in binary or grayscale images. Dilation is commonly used for noise removal, object enhancement, filling gaps in contours, and connecting nearby objects. The operation uses a structuring element (kernel) that defines the shape and size of the dilation. Essential for image preprocessing in computer vision applications, medical imaging, and object detection. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVEdgeDetectBlock

OpenCV edge detection block for identifying boundaries and contours in video streams. This block performs edge detection using various computer vision algorithms including Canny, Sobel, Laplacian, and Scharr operators. Edge detection is fundamental for object recognition, feature extraction, image segmentation, and computer vision applications. The block provides configurable threshold parameters, gradient calculations, and noise reduction capabilities. Essential for medical imaging, industrial inspection, autonomous vehicles, and surveillance systems. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVEqualizeHistogramBlock

OpenCV histogram equalization block for automatic image contrast enhancement. This block performs histogram equalization to improve image contrast by redistributing pixel intensities across the full dynamic range. The algorithm analyzes the image histogram and applies a transformation that spreads out the most frequent intensity values, resulting in enhanced visual quality. Essential for medical imaging, surveillance systems, and low-light video enhancement where contrast improvement is critical for analysis. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVErodeBlock

OpenCV erode block for morphological image processing operations. This block performs erosion, a fundamental morphological operation that shrinks white regions (foreground objects) in binary or grayscale images. Erosion is commonly used for noise removal, thin line detection, separating connected objects, and removing small artifacts. The operation uses a structuring element (kernel) that defines the shape and size of the erosion. Often paired with dilation for opening/closing operations in computer vision preprocessing. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVFaceBlurBlock

OpenCV face blur block for automatic privacy protection in video streams. This block combines face detection with blur effects to automatically obscure faces for privacy compliance. Uses machine learning algorithms to detect human faces in real-time and applies configurable blur effects to protect individual privacy. Essential for surveillance systems, social media platforms, and video conferencing applications where privacy regulations require face anonymization. Supports multiple blur algorithms and adjustable detection sensitivity for various lighting conditions. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVFaceDetectBlock

OpenCV face detection block for identifying and tracking human faces in video streams. This block uses advanced computer vision algorithms including Haar cascades, LBP (Local Binary Patterns), and deep learning models to detect faces in real-time. Provides configurable detection parameters, face tracking capabilities, and event notifications when faces are found. Essential for security systems, attendance tracking, emotion recognition, and interactive applications. Supports multiple face detection simultaneously with bounding box coordinates and confidence scores. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVHandDetectBlock

OpenCV hand detection block for identifying and tracking human hands in video streams. This block uses computer vision algorithms to detect hand positions, gestures, and movements in real-time video. Supports gesture recognition, hand tracking for interactive applications, sign language processing, and touchless user interfaces. Uses machine learning models trained on hand features to provide accurate detection across various lighting conditions and hand poses. Essential for gesture-controlled systems, accessibility applications, and human-computer interaction. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVLaplaceBlock

OpenCV Laplacian edge detection block for advanced image analysis and feature extraction. This block applies the Laplacian operator to detect edges and rapid intensity changes in video frames. The Laplacian is a second-order derivative operator that's particularly effective at finding edge discontinuities and fine details. Often used in image sharpening, blob detection, and computer vision applications where edge definition is critical. Provides configurable kernel sizes and normalization options for different image types and analysis requirements. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVMotionCellsBlock

OpenCV motion detection block for intelligent surveillance and movement analysis. This block divides the video frame into a grid of cells and detects motion within each cell, providing fine-grained motion analysis capabilities. Uses background subtraction and frame differencing algorithms to identify moving objects and track motion patterns. Essential for security systems, traffic monitoring, and automated surveillance applications. Provides configurable sensitivity, region-of-interest selection, and motion event notifications. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVSmoothBlock

OpenCV smoothing block for image noise reduction and blur effects. This block applies various smoothing algorithms including Gaussian blur, box filter, bilateral filter, and median blur to reduce noise and soften image details. Essential for preprocessing operations in computer vision pipelines, medical imaging, and artistic effects. Provides configurable kernel sizes, sigma values, and edge preservation options. Commonly used to reduce sensor noise, prepare images for edge detection, or create aesthetic blur effects in video production. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVSobelBlock

OpenCV Sobel edge detection block for gradient-based image analysis. This block applies the Sobel operator to detect edges by calculating image gradients in horizontal and vertical directions. The Sobel filter is particularly effective for edge detection in noisy images due to its built-in smoothing capabilities. Provides separate X and Y gradient calculations, magnitude computation, and directional filtering options. Essential for computer vision applications, feature extraction, and image preprocessing where robust edge detection is required. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVTemplateMatchBlock

OpenCV template matching block for object detection and pattern recognition. This block searches for specific template images within the video stream using various correlation algorithms including normalized cross-correlation, squared difference, and correlation coefficient methods. Essential for automated inspection, object tracking, quality control, and computer vision applications where specific patterns or objects need to be located. Provides configurable matching algorithms, threshold settings, and multiple match detection capabilities. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVTextOverlayBlock

OpenCV text overlay block for advanced text rendering and annotation in video streams. This block provides sophisticated text overlay capabilities using OpenCV's text rendering functions, supporting various fonts, styles, colors, and positioning options. Offers anti-aliasing, outline effects, shadow rendering, and Unicode text support. Essential for video annotation, subtitles, watermarking, and information display applications. Provides real-time text updates, dynamic positioning, and professional-quality typography. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.

CVTrackerBlock

OpenCV object tracking block for continuous monitoring of moving objects in video streams. This block implements advanced tracking algorithms including KCF (Kernelized Correlation Filters), CSRT (Channel and Spatial Reliability Tracker), Median Flow, and MIL (Multiple Instance Learning) trackers. Provides robust object tracking capabilities for surveillance, sports analysis, autonomous vehicles, and interactive applications. Supports initialization from bounding boxes, adaptive model updates, and tracking confidence reporting. Essential for maintaining object identity across frames despite occlusions, scale changes, and appearance variations. Implements the VisioForge.Core.MediaBlocks.MediaBlock. Implements the VisioForge.Core.MediaBlocks.IMediaBlockInternals. Implements the IDisposable.