Abstract
This chapter describes machine vision and focuses on object recognition. It describes the machine how to recognize the objects and react differently depending on the object classes. Object recognition is further divided into image classification, object localization, and object detection. Compared with the traditional computer vision algorithmic approach, convolutional neural network does not require defining the object features and performing one-to-one matching. It offers better feature extraction and matching than algorithmic strategies. The gesture-based interface allows the user to control different devices using hand or body motion. The chapter introduces several important machine vision applications in different areas, including medical diagnosis, retail applications, and airport security. Retail also benefits from machine vision, which teaches the machine to recognize the items in the images and videos. Facial recognition is an important airport security application, especially for passenger processing.
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