ICPRIP 2026: International Conference on Pattern Recognition and Image Processing

ICPRIP 2026: International Conference on Pattern Recognition and Image Processing focuses on pattern recognition and image processing, addressing image analysis algorithms, computer vision techniques, medical imaging, object recognition, machine learning for vision, and advanced modeling and representation methods.

Key Topics

• Image-based modeling and algorithms
• Software tools for imaging
• Motion and tracking algorithms + orientation estimation
• Illumination and reflectance modeling
• Event recognition techniques in image sequences
• Biometric authentication
• Image geometry and multi-view geometry
• Medical image processing and analysis
• Geometric modeling and fractals
• Segmentation techniques
• Image data structures and databases
• Scene and object modeling
• Image display techniques
• Image compression, coding, and encryption
• Image formation techniques
• Digital imaging for film and television
• Image feature extraction
• Image generation, acquisition, and processing
• Enhancement techniques
• Novel document image understanding techniques + OCR
• Mathematical morphology
• Novel noise reduction algorithms
• Watermarking methods and protection
• 3D imaging
• Wavelets, data hiding, image copyright and related issues
• Wavelet methods
• Color and texture
• Mosaic, image registration and fusion methods
• Image restoration
• AI, machine learning, SVT with applications in imaging science
• Interpolation techniques
• Printing technologies
• Video analysis
• Shape representation
• Signal and speech processing
• Indexing and retrieval of images (image databases)
• Multi-resolution vision techniques
• Object recognition
• Stereo vision
• Face recognition, face detection, and gesture recognition
• Machine learning technologies for vision
• Soft computing methods in image processing and vision
• Camera networks and vision
• Performance analysis and evaluation (real-time vision)
• Active and robot vision
• Sensors and early vision
• Fuzzy and neural techniques in vision
• Cognitive and biologically inspired vision
• Special-purpose machine architectures for vision
• Graph theory in image processing and vision
• Classification and clustering techniques
• Dimensionality reduction methods in pattern recognition
• Statistical pattern recognition
• Symbolic learning
• Knowledge-based recognition
• Invariance in pattern recognition