What Is Object Recognition?
Object recognition is a process for identifying a specific object in a digital image or video. Object recognition algorithms rely on matching, learning, or pattern recognition algorithms using appearance-based or feature-based techniques.
Object recognition is useful in applications such as video stabilization, advanced driver assistance systems (ADAS), and disease identification in bioimaging. Common techniques include deep learning based approaches such as convolutional neural networks, and feature-based approaches using edges, gradients, histogram of oriented gradients (HOG), Haar wavelets, and linear binary patterns.
Object Recognition Techniques
You can recognize objects using a variety of models, including:
- Feature extraction and machine learning models
- Deep learning models such as CNNs
- Bag-of-words models with features such as SURF and MSER
- Gradient-based and derivative-based matching approaches
- The Viola-Jones algorithm, which can be used to recognize a variety of objects, including faces and upper bodies
- Template matching
- Image segmentation and blob analysis