Trace transform based method for color image domain identification

TL;DR

This paper introduces a new color image context categorization method called DITEC, which uses trace transform and statistical descriptors to effectively reduce dimensionality and improve content discrimination.

Contribution

The paper presents a novel trace transform based approach for color image domain identification, with a focus on effective dimensionality reduction and discriminant feature extraction.

Findings

Method is validated on two datasets.

Features demonstrate high discriminant power.

Theoretical analysis supports practical effectiveness.

Abstract

Context categorization is a fundamental pre-requisite for multi-domain multimedia content analysis applications in order to manage contextual information in an efficient manner. In this paper, we introduce a new color image context categorization method (DITEC) based on the trace transform. The problem of dimensionality reduction of the obtained trace transform signal is addressed through statistical descriptors that keep the underlying information. These extracted features offer a highly discriminant behavior for content categorization. The theoretical properties of the method are analyzed and validated experimentally through two different datasets.