Open AccessImage Description Using the Relation Between Color and Texture in Retrieval Task
Author(s) -
Kevin Salvador Aguilar-Domínguez,
Raúl Pinto-Elías,
Juan Gabriel González Serna,
Andrea Magadán-Salazar
Publication year - 2022
Publication title -
traitement du signal/ts. traitement du signal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.279
H-Index - 11
eISSN - 1958-5608
pISSN - 0765-0019
DOI - 10.18280/ts.390103
Subject(s) - texture (cosmology) , artificial intelligence , computer science , image retrieval , pattern recognition (psychology) , task (project management) , relation (database) , image (mathematics) , image texture , computer vision , information retrieval , image processing , data mining , management , economics
In the past years, significant efforts have been made for new theories and models of descriptors for Content-Based Image Retrieval systems and many effective descriptors, which use color and texture, have been established. This article presents the analysis and modifications of descriptors that use color and texture for the image retrieval task. To provide a complete detailed, and fair analysis, exposing weaknesses in descriptors and ideas to correct them. We evaluated descriptors that use color and texture, with image sets and metrics found in the literature. We compared classical descriptors that only use one low-level characteristic with descriptors that use color and texture. The analysis showed discrepancies between the model and the implementation of one of the descriptors, as well as the descriptors with the best performance, their main weaknesses, and complications when we trying to correct them. likewise, we present variants that improve the image retrieval in some cases.