Feature Extraction for Image Processing and Computer Vision- a Comparative Approach

EasyChair Preprint 7397

Abstract

Digital Image processing is a technique to process image digitally. This means image is represented using pixels and all the algorithm are implemented using that value.A digital image consists of a finite variety of parts unremarkably named as image parts, pixels. Pixel value determines the type of image ie weather it is gray scale or RGB . Computer Vision is a part of deep learning in which processiong is done on images.The application of image processing include robotics,object detection, weather forecating etc.In this paper the main goal is to focus on different feature extraction techniques applied by compourt vision and digital image processing.Image Features are important input for any image processing tasks.Features include Blobs,Corner ,Edges etc.

Keyphrases: Artificial Intelligence, Pixel, SIFT, image processing

@booklet{EasyChair:7397,
  author    = {Radha Seelaboyina and Rajeev Vishwkarma},
  title     = {Feature Extraction for Image Processing and Computer Vision- a Comparative Approach},
  howpublished = {EasyChair Preprint 7397},
  year      = {EasyChair, 2022}}