Many of us know about Computer Vision and Image Recognition. But the difference is not clear and the words can be used interchangeably. Computer Vision, developed by many AI developers, allows a computer to imitate human vision. After that, discoveries are stored and actions are then taken accordingly. Image Recognition, on the other hand, is the analysis of the pixels and patterns of an image. As a result, a particular object can be recognized.
We, as humans, can recognize the difference between a cat, dog or an apple. But the process of recognition is hard for a computer in its initial stage.
Image Recognition is the ability of a computer to identify and detect the features of an image or objects. In short, it includes the processes of capturing, processing, examining and sympathizing images. Computers use machine vision technology powered by the Artificial Intelligence System.
Image Recognition Process
How does it work? How a computer can distinguish between any two images? The following are the steps for image recognition.
Step 1: Features are a number of characteristics which can be extracted from the given image. Pixels make up the image. It represents a number or set of numbers. Color depth is the range of pixels. Therefore, the color depth specifies the maximum number of potential colors that can be used in the image.
Step 2: The images are converted into features, labelled and then, grouped in different categories. When more images are added, the computer can be trained better to recognize an image.
Step 3: Pre-labelled images help train the computer. When a computer is made to recognize an image, the extracted form of this image is entered as an input. On the other hand, the labels are in the output side. The computer is then made to differentiate the image with its features coming from the input with the labels in the output.
Step 4: A trained computer can recognize any unknown image. The new image will go through the pixel feature extraction process.
In the commercial world, major applications of image recognition are face recognition, security and surveillance, object recognition, image analysis in medical field, etc. E-commerce also use image recognition in search and advertising. It helps in an interactive world by making searches easier. Advancements in the various industries were possible by computer vision technology using AI image recognition.
The new AI chip
The artificial eye is the combination of light-sensing electronics with a neural network on a single tiny chip. It can perform the image recognition process in nanoseconds, faster than the existing image sensors.
Most image recognition process takes a lot of computing power to work. The huge amount of data collected slows down the recognition process. However, a sensor that captures and processes the image at the same time is much faster with less power. This new sensor is an exciting new thing. It sets the path for the movement of the AI into hardware, consequently making the process quick and efficient.
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