📸 Image Processing using OpenCV (Python)

This project demonstrates various image processing techniques using OpenCV and Python.
It includes basic operations such as image loading, resizing, color conversions, filtering, edge detection, thresholding, morphological operations, and more.

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🧰 Technologies Used

• Python 3.x
• OpenCV (cv2)
• NumPy
• Matplotlib (optional for visualization)

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📂 Project Structure

├── images/ # Input images ├── outputs/ # Processed results ├── src/ │ ├── basic_operations.py │ ├── filters.py │ ├── edge_detection.py │ ├── thresholding.py │ ├── morphology.py │ └── utils.py └── README.md

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✨ Features

✔️ Basic Operations

• Load, display, and save images
• Resize, rotate, crop
• Convert to grayscale
• Draw shapes and add text

✔️ Image Filtering

• Gaussian Blur
• Median Filter
• Bilateral Filter
• Custom convolution filters

✔️ Edge Detection

• Sobel operator
• Prewitt (custom)
• Scharr
• Canny edge detector

✔️ Thresholding

• Global thresholding
• Adaptive thresholding
• Otsu’s binarization

✔️ Morphological Operations

• Erosion
• Dilation
• Opening & Closing
• Morphological Gradient

✔️ Additional Modules

• Histogram equalization
• Contour detection
• Image segmentation

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🚀 Getting Started

1️⃣ Install Dependencies

pip install opencv-python numpy matplotlib 2️⃣ Clone This Repository bash Copier le code git clone https://github.com/your-username/image-processing-opencv.git cd image-processing-opencv 3️⃣ Run a Script bash Copier le code python src/basic_operations.py 🧪 Example Usage python Copier le code import cv2

Load an image

img = cv2.imread("images/lena.png")

Convert to grayscale

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

Apply Gaussian Blur

blur = cv2.GaussianBlur(gray, (5, 5), 0)

Display the result

cv2.imshow("Blurred Image", blur) cv2.waitKey(0) cv2.destroyAllWindows()

📘 Useful Documentation

OpenCV Docs: https://docs.opencv.org

NumPy Docs: https://numpy.org/doc

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