About image recognition and how is it used?

Machine learning image recognition

Image recognition is one of the latest technologies which are used for identifying photos, images, objects, logos and several other things in the images. These days users are sharing vast amount of data using social networking websites, applications etc. Along with it, mobile phones built in with camera are also used for creation of digital images and videos. Considering vast use of images and videos by users, various companies have emerged to provide better and smart way of digital data services.

What is image recognition?
Image recognition is offered by computers, wherein objects or attributes in digital video or images are identified. Machine learning image recognition method is usually used for gathering, processing and analyzing images saved in the real world. While processing and analyzing the data, various numerical and symbolical information is produced which is further useful for taking big decisions. Apart from image recognition various other services are offered which includes object recognition, reconstruction of image and also video tracking.

How does image recognition works?
Image recognition is performed by various companies these days. Even Facebook the most popular social networking website is capable of recognizing image to an accuracy of approx. 95%. Facebook can even detect your friends with some of the tagged pictures in your account. One should make a note that the capacity of recognizing images more or less depends on the kind of technology used and how images are classified. For companies to ensure that image recognition takes place in the most effective manner, they can approach machine learning image Recognition Company and avail services to achieve maximum benefits.

Gather and organize the data
For image recognition human eyes observes the image and set signals which is further processed by visual cortex of brain. This helps in creating vivid experience of the scene and objects associated to it. Similar process is being copied by the machine at the time of recognizing image. Machine perceives an image as raster or vector image. While raster image is a sequence of pixels with unique numerical value and color, vector image is a se of colored polygons. To analyze the images, the geometric coding is done and then transformed as per physical feature of the object.

Once image has been analyzed then data is organized to further perform classification and extraction. Image classification involves a series of steps as mentioned below;

  1. The first step towards classification is simplifying the image and then extracting important portions out of it.
  2. Edge detector is one of the most useful methods which helps identify main portions of an image i.e. face and eyes. The important portions are detected and rest of it is thrown away.
  3. Various other descriptor techniques are also available in the market which includes Scale invariant feature transform, histogram of oriented gradients etc.
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Once data is classified, based on a predictive model further image is studied and then recognized for various purposes. Various kinds of image classification and recognizing models are available; to ensure that the most accurate result is produced one must invest in the best and latest technology available in the market.

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About the author: Jitender Sharma

I am Jitender Sharma founder of Basictutorialonline.com and managing over 20+ other blogs, websites and services. I am a Pro Blogger and Professional SEO & Digital Marketing Consultant.

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