Tech Stack
ANN
LBP
Feature Engineering
Image Classification
HOG
Description
Performed a comprehensive comparative analysis of machine learning classifiers for handwritten mathematical symbol recognition using a dataset of mathematical characters.
Implemented and evaluated multiple feature extraction techniques including Gabor filters, Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP), and normalized raw pixel representations.
- The SVM with Gabor filter features delivered optimal performance at 98.9% accuracy
- Highlighted Gabor's strength in capturing edge orientations and spatial frequency patterns
- Enhanced expertise in feature engineering and classifier comparison