Image recognition is a sub-field of Computer Vision that focuses on analyzing and identifying images to place them into distinct categories or give them selected properties. Usually, categories are based on the object, person, place, or logo that the image contains.
The most popular tasks of Image recognition, closely similar to Computer Vision in total, are classification, segmentation, detection, and tagging. Computer Vision, however, apart from image recognition, also covers other topics and tasks, such as gathering and organizing the data and fields of image enhancement, event detection, and others.
The most popular method in Image recognition is Deep Learning and Neural Networks, but some simpler tools are also common for easier tasks. After processing the image, systems perform feature extraction, learning the most representative details about the object.
To do so, the algorithms usually need to be trained on many images of different categories, with the number being in the thousands. Based on this information, the system decides if the image belongs to the category or not.
Why is it important?
The importance of Image recognition is in giving computers and machines the ability to recognize many everyday objects on images. This allows computers to understand the context or further analyze the image and draw conclusions from it. In turn, it allows automating the business processes, as based on what was recognized the respective action can be performed.