Election Digit Scanner
Nail handwritten digit recognition for 2024 Indonesia vote recaps with HOG and SVM.
Project Description
This project kills data entry errors in the 2024 Indonesian Presidential Election vote recap with cutting-edge pattern recognition.
Uses Histogram of Oriented Gradients (HOG) for feature extraction and K-Nearest Neighbors (KNN) plus Support Vector Machine (SVM) for classification, hitting over 97% accuracy.
Experiments prove HOG + SVM is the champ, delivering top-tier performance across dataset splits.
Key Features
HOG Feature Magic
Extracts edges and gradients for pinpoint digit recognition.
SVM & KNN Power
Drops 97%+ accuracy with killer classification algorithms.
Performance Breakdown
Compares extraction vs. no-extraction for clear wins.
Technical Details
Python
Versatile programming language for web development, data science, and automation
HOG
Histogram of Oriented Gradients for object detection
SVM
Support Vector Machines for classification and regression tasks
KNN
K-Nearest Neighbors for classification based on distance metrics