# Gabor Wavelets in Image Processing

arXiv: https://arxiv.org/abs/1602.03308 · HTML: https://mlsanity.com/paper/1602.03308/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Feb 2016.

## Built on by (most cited first, 2 of 2)

- [Single Object Tracking: A Survey of Methods, Datasets, and Evaluation Metrics](https://mlsanity.com/paper/2201.13066/) (2022)
- [MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles](https://mlsanity.com/paper/2310.05290/) (2023)

## Abstract (arXiv)

This work shows the use of a two-dimensional Gabor wavelets in image processing. Convolution with such a two-dimensional wavelet can be separated into two series of one-dimensional ones. The key idea of this work is to utilize a Gabor wavelet as a multiscale partial differential operator of a given order. Gabor wavelets are used here to detect edges, corners and blobs. A performance of such an interest point detector is compared to detectors utilizing a Haar wavelet and a derivative of a Gaussian function. The proposed approach may be useful when a fast implementation of the Gabor transform is available or when the transform is already precomputed.