In this article, we will consider the image recognition meaning. As well as the existence of the application for this technology.
What Is Image Recognition?
Image recognition meaning is identifying and describing objects and patterns in the image.
Image recognition has many applications. Such as the following:
- Advertising
- Transportation
- Games
- Business
- law enforcement and others
For example, it can be used to recognize faces in a photo or video. To draw conclusions about the emotional state of the person smiling, sad, etc. Also, it can detect signs and text.
How Does Image Recognition Work?
Image recognition is a complex process, which requires a powerful computer and a large number of additional algorithms.
The algorithm for image recognition must first identify the objects contained in the image. This is done by comparing the input image with a set of reference images.
On this basis, you can perform a detailed characterization of the image – to identify specific objects and describe them in detail.
Image recognition works with the help of neural networks. In this case, each network is designed to recognize one or more patterns
The result of their joint work is the conclusion that the image contains such and such objects.
Applications And Examples Of Image Recognition
Applications and examples of image recognition are the following:
1) Face recognition:
Face recognition is one of the most common and useful applications of this technology. It can be used for immediate identification or verification of identity.
2) OCR (Optical Character Recognition)
OCR is used to recognize text in images and convert it into meaningful information. The simplest example of this technology is Google Translate. Which reads text from images and translates it into different languages.
3) Text detection
Text detection is used to detect the presence and position of text in an image so that you can perform further processing on it. Such as optical character recognition.
4) Image classification.
Classification allows you to assign an object to one or more classes according to certain characteristics. For example, you can take an image with many unknown plants, classify them according to their size and color, select those plants. Especially those that are poisonous, and delete all others from the viewfinder.
5) Image segmentation
Segmentation will allow you to divide an image into several parts. So hat have different properties – for example, color or texture.
6) Face tracking
Face tracking allows us to track changes in facial expression – for example, changes in emotional state (smiling/pouting), eye movement or head motion (turning his head).
7) Landmark Tracking
Landmark tracking serves not only as means of image segmentation. But also as a way to track the movement of an object in the image.
For example, moving objects can be tracked using this technique.
8) Image stabilization
Image stabilization is used to correct camera shake in images. Thus, it is most often used in video recording. Image stabilization allows you to remove small vibrations and improve the quality of the recorded video.
9) Object detection.
Object detection is one of the most common ways of using image recognition technology. So, it allows you to find an object in the image, track it and determine its position.
This can be applied to many areas that include: finding people, vehicles, animals, finding specific objects, etc.
10) Face Detection in Images And Video
Monitoring for people in images and video is one of the most important applications of image recognition technology. Applications for this technology include security control.
