IMCV 🚀

Overview

A collection of fundamental Signal Processing, Image Processing, and Computer Vision (IMCV) algorithms implemented from scratch. This repository serves as a portfolio piece and a hands-on educational resource for understanding the core mechanics behind these powerful techniques without relying on high-level library (wherever applicable).

IMCV collections:

• 📶 Signal Processing
• 🖼️ Image Processing
• 👁️ Computer Vision

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🎯 Objectives

• Reinforce low-level understanding of essential DSP/IP/CV algorithms.
• Build a practical and visual portfolio to demonstrate technical skills.
• Provide a learning reference for students and professionals alike.

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✅ Implemented Algorithms Roadmap

📶 Signal Processing

Spatial Frequency Domain

• [] Spatial Frequency

Fourier Analysis

• Discrete Fourier Transform (DFT)
• Fast Fourier Transform (FFT)

Filtering

• Low-Pass Filters (e.g., Moving Average)
• High-Pass Filters

Convolution

• 1D Convolution

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🖼️ Image Processing

Core Operations

• Grayscale Conversion
• Brightness & Contrast Adjustment

Image Filtering & Enhancement

• Gaussian Blur
• Sharpening Kernels
• Median Filter

Edge Detection

• Sobel Operator
• Prewitt Operator
• Canny Edge Detector

Histogram Manipulation

• Histogram Generation
• Histogram Equalization

Geometric Transformations

• Image Resizing (Nearest Neighbor, Bilinear Interpolation)
• Rotation
• Cropping

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👁️ Computer Vision

Feature Detection & Description

• Harris Corner Detection
• (Conceptual) Scale-Invariant Feature Transform (SIFT)

Image Segmentation

• Binary Thresholding (Otsu's Method)
• K-Means Color Clustering

Object Recognition

• Template Matching