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Classification
Classification is the process of determining the class or category of an input image. The input image is analysed
using a Machine Learning Algorithm, which assigns it to one of the predefined categories. These categories are
established by training the algorithm on a set of labelled sample images. This foundational task in Computer Vision
has numerous practical applications, such as medical diagnostics, object recognition and autonomous vehicles.
Classification and Localisation
Localisation means where the object is located in the image. So, this combined task of classification and localisation
means processing the input image to identify its category along with the location of the object in the image.
Multiple Objects
This means giving multiple images as input to the Computer Vision application. It can be further divided into two
categories i.e. object detection and instance segmentation.
Object Detection
Object detection is the process of identifying or detecting the instances of real-world objects like cars, bicycles,
buses, animals, humans, or anything on which the detection model has been trained. This kind of system uses
object detection algorithms to extract the features of the object and after that Machine Learning Algorithms will
recognise the instances of an object category by matching it with the sample images already fed into the system.
It is commonly used in applications such as image retrieval and automated vehicle parking systems.
Instance Segmentation
Instance segmentation is the process of dividing an image into smaller segments to identify individual objects
within it, distinguishing them from the background or other objects in the image. Each object instance is
detected, classified, and assigned a unique label. Following this, every pixel in the image is labelled based on the
corresponding object instance it belongs to. A segmentation algorithm takes an image as input and outputs a
collection of regions (or segments).
Another example of Computer Vision analysis can be seen as follows:
Classification Instance
Classification Object Detection
+ Localisation Segmentation
CAT CAT DOG, CAT DOG, CAT
Single object Multiple objects
Basics of Images
An image is a visual representation of any object. The term ‘image’ means a picture that has been created or
stored in electronic form. It can be described in terms of vector graphics or raster graphics. An image comprises
of a rectangular array of dots known as pixel. The size of the image is specified as width × height, in the number
of pixels.
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