Imagine someone took a picture of you in the street. After examining the image, a person somehow finds out who you are, your personal details and social media contacts. Sounds creepy, doesn’t it? Someone has just used image recognition to find something about you. Let’s find out what it is and the threats and possibilities of it.
Image recognition is when computers recognize and identify the elements making up an image. These can include people, objects, events etc.
It does so by imitating the way we perceive visual information using artificial intelligence, machine learning and neural networks to process, interpret and classify visual information.
An image is divided into small particles called pixels. A machine understands an image as a matrix of numerical values. These values represent the information pixels contain (e.g., colors). By analyzing the visual info contained in pixels, their positions and patterns, the system can begin to understand an image. For example, the data patterns detected in certain sections of an image can identify it as the face of a human being.
Machine learning (ML) can empower image recognition technology by enabling devices to process large amounts of data and learn from it.
It starts by feeding lots of pictures with attributed labels into the system. For example, if we want to identify human beings in images, we give the system images with and without human beings and label them accordingly. As a result, it will start to understand patterns and recognize human beings in images presented to it in the future. This type of “education” requires tens of thousands of images, making it a resource-intensive process.
We can apply image recognition in a wide number of areas:
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