Edge detection in machine vision refers to the technique of identifying boundaries within images by detecting discontinuities in pixel intensity. An edge detection algorithm is used to locate these transitions, which typically correspond to object boundaries, texture changes, or abrupt shifts in the scene. One of the most commonly used edge detection algorithms is the Canny edge detector. It works by first applying a Gaussian filter to smooth the image, then calculating gradients to detect changes in intensity, followed by non-maximum suppression to refine the edges, and finally, edge tracing by hysteresis. Other algorithms include the Sobel operator, which highlights edges in a specific direction, and the Prewitt operator, which works similarly but uses different convolution masks. These edge detection techniques are widely used in various applications, such as identifying objects in images, aiding in image segmentation, or processing images for object tracking. Edge detection plays a critical role in simplifying image analysis by focusing only on the most important features—edges—making it easier to process the image further in computer vision tasks.
What is a machine vision edge detection algorithm?
- Getting Started with Milvus
- AI & Machine Learning
- Information Retrieval 101
- Mastering Audio AI
- Retrieval Augmented Generation (RAG) 101
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
How does a typical ETL architecture look for a data warehouse?
A typical ETL (Extract, Transform, Load) architecture for a data warehouse consists of three core stages, supported by t
What are the best tools for data synchronization?
Data synchronization is critical for ensuring that information remains consistent across various systems. The best tools
What are the challenges in applying Explainable AI to deep learning?
Applying Explainable AI (XAI) to deep learning presents several challenges that stem primarily from the complexity and o