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Image and Video Annotations: What is a Bounding Box?

When it comes to collecting and analyzing data in images and videos, one of the most efficient tools is the bounding box. Focus on these helpful imaginary boxes.

Image and Video Annotations: What is a Bounding Box?

AI and machine learning use various digital methods and tools meant to help with Image Annotation, one of them being using bounding boxes.

Let’s dig a little deeper and answer the following question: what is a bounding box, or bbox?

What is a bounding box in image processing?

A bbox is a rectangle defined by x (or longitude) and y (or latitude) coordinates, whose edges surround a specific item. It is used in Image Processing to determine the spatial position of an object in the image. The coordinates are determined by the upper-left-hand corner and the lower-right corner of the image.

Dimensions of a bbox might vary, depending on the width and height of the different items, for example, a car versus a bicycle. A Bbox is drawn by data annotators on a single image, or on each image of a provided sequence. A machine learning algorithm can then be trained to perform object detection: to identify object bounding boxes in images. For small objects, a minimum bounding box is needed, with minimum width and height.

After drawing the bounding boxes, an annotator may label it with the name of the object in order to make it quickly recognizable. Usually, the labels are assigned to different colors.

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What is bounding box annotation used for?

Bbox technique has many functions, but the most important functionality is object detection. Thanks to the settings done when annotating the boxes on the set of images provided, computer vision algorithms can recognize instantly that these elements look just like the references it was given previously. It will then display them on the screen with their affected colors.

The accuracy of a machine-learning-powered object detection algorithm not only relies on the width and height of the polygon which surrounds the element. It also shows a better result when you have a wide array of object categories. The more references the machine learning system is given, the better it is for the computer to know what it has to analyze. This method is deployed for various uses and is available on different software.

This object detection  technology is used in various fields:

  • Self-driving cars' cameras and AI systems to prevent accidents.

  • Insurance claims when they want to know what caused an accident.

  • Agriculture companies and farmers in order to detect the presence of parasites or diseases on their plants.

  • Healthcare to detect if bacteria or viruses have progressed or not.

  • eCommerce companies to offer a better experience to customers.

In most cases, companies use bounding boxes for object detection. But bbox techniques are also used on various computer settings and software to transform, align, scale objects, or modify their orientation. That is the case with Adobe Photoshop, Illustrator, or Microsoft’s Powerpoint.

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