A Modified Image Comparison Algorithm Using Histogram Features

TL;DR

This paper introduces a modified image comparison algorithm that leverages color histograms and spatial information, achieving high accuracy while maintaining scale and rotation invariance.

Contribution

The paper proposes a novel image comparison method that incorporates color location into histogram features, improving accuracy over traditional histogram-based methods.

Findings

Achieves 97% average precision on a 700-image dataset.

Maintains scale and rotation invariance.

Outperforms traditional histogram methods in content comparison.

Abstract

This article discuss the problem of color image content comparison. Particularly, methods of image content comparison are analyzed, restrictions of color histogram are described and a modified method of images content comparison is proposed. This method uses the color histograms and considers color locations. Testing and analyzing of based and modified algorithms are performed. The modified method shows 97% average precision for a collection containing about 700 images without loss of the advantages of based method, i.e. scale and rotation invariant.