Image feature extraction algorithm for support vector machines using multi-layer block model

Keyphrases

• Computational Load 100%
• Support Vector Machine 100%
• Feature Extraction Methods 100%
• Recognition Performance 100%
• Local Features 100%
• Block Model 100%
• Image Feature Extraction 100%
• Feature Extraction 50%
• Over 80 50%
• Three-dimensional (3D) 50%
• Kernel-based 50%
• Feature Extracting 50%
• Extraction Methods 50%
• Feature Information 50%
• Overlapping Blocks 50%
• Recognition Rate 50%
• Noisy Conditions 50%
• 3-step 50%
• Illumination Conditions 50%
• Varying Illumination 50%
• Hierarchical Layer 50%
• Enhanced System 50%
• Proposed Feature Extraction 50%
• Low-dimensional Feature Space 50%
• System Recognition 50%

Computer Science

• Support Vector Machine 100%
• image feature 100%
• Feature Extraction 100%
• Computational Load 66%
• Recognition Performance 66%
• local feature 66%
• Dimensional Object 33%
• Feature Information 33%
• Recognition Rate 33%
• Dimensional Feature Space 33%
• Varying Illumination 33%

Engineering

• Feature Extraction 100%
• Support Vector Machine 100%
• Computational Load 66%
• Isolation Method 66%
• Simulation Result 33%
• Block Basis 33%
• Input Image 33%
• Recognition Rate 33%
• Extracted Feature 33%
• Dimensional Feature Space 33%
• Hierarchical Block 33%