# Comparative analysis of common edge detection techniques in context of object extraction

arXiv: https://arxiv.org/abs/1405.6132 · HTML: https://mlsanity.com/paper/1405.6132/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Feb 2014.

## Built on by (most cited first, 3 of 3)

- [Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images](https://mlsanity.com/paper/2102.06883/) (2021)
- [Vision-Based Incoming Traffic Estimator Using Deep Neural Network on General Purpose Embedded Hardware](https://mlsanity.com/paper/2311.16125/) (2023)
- [Edge-oriented Implicit Neural Representation with Channel Tuning](https://mlsanity.com/paper/2209.11697/) (2022)

## Abstract (arXiv)

Edges characterize boundaries and are therefore a problem of practical importance in remote sensing.In this paper a comparative study of various edge detection techniques and band wise analysis of these algorithms in the context of object extraction with regard to remote sensing satellite images from the Indian Remote Sensing Satellite (IRS) sensors LISS 3, LISS 4 and Cartosat1 as well as Google Earth is presented.