Computer Vision dengan OpenCV dan Python

Computer Vision memungkinkan komputer interpret dan understand visual world. OpenCV (Open Source Computer Vision Library) adalah library paling populer, ditulis C++ dengan bindings Python, Java, MATLAB. Core capabilities: image processing (filtering, transformations, morphology), feature detection (edges, corners, blobs), object detection (Haar Cascades, HOG), object tracking, camera calibration, stereo vision, dan machine learning integration. Installation: pip install opencv-python opencv-contrib-python. Basic operations: read/write images, color space conversion (BGR, RGB, HSV, grayscale), resizing, cropping, rotation, blurring (Gaussian, median), edge detection (Canny), thresholding. Advanced techniques: contour detection untuk shape analysis, morphological operations (erosion, dilation, opening, closing), histogram equalization untuk enhance contrast, template matching. Object detection: Haar Cascade classifiers untuk face/eye detection (real-time, lightweight tapi kurang akurat), HOG (Histogram of Oriented Gradients) dengan SVM untuk pedestrian detection, deep learning models (YOLO, SSD, Faster R-CNN) untuk multi-object detection dengan high accuracy. Face recognition: dlib dengan face_recognition library, FaceNet embeddings. Optical Character Recognition: Tesseract integration untuk text extraction dari images. Video processing: frame extraction, object tracking (KCF, CSRT, MedianFlow algorithms), motion detection. Real-world applications: autonomous vehicles (lane detection, traffic sign recognition), surveillance systems, medical imaging (tumor detection), quality inspection dalam manufacturing, augmented reality, dan gesture recognition. Integration dengan deep learning: use pre-trained models (TensorFlow, PyTorch), custom training dengan transfer learning. Performance optimization: GPU acceleration dengan CUDA, image pyramid untuk multi-scale detection, ROI (Region of Interest) processing. Challenges: lighting variations, occlusions, viewpoint changes, real-time processing constraints. Projects ideas: face attendance system, license plate recognition, document scanner, emotion detection, pose estimation. OpenCV ecosystem mature dengan extensive documentation dan active community.