Significance of the Background Image Texture in CBIR System

Autor:	S. R. Pattanaik, Charulata Palai, Pradeep Kumar Jena
Rok vydání:	2019
Předmět:	Feature (computer vision) business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Artificial intelligence Content-based image retrieval Texture feature business Texture (geology) Distance measures Background image Image (mathematics)
Zdroj:	Advances in Intelligent Systems and Computing ISBN: 9789811386756
DOI:	10.1007/978-981-13-8676-3_42
Popis:	The Content Based Image Retrieval (CBIR) using local texture feature is extensively studied for decades. The local texture features such as LBP, LTP, LDP, and other derived local texture features uniquely describes the content of an image. The performances of the local texture features with different classifiers are well exposed by the researchers. The purpose of this paper is to explore the effect of the LBP texture feature due to simple and complex background in the image. The experiments are done with the Wang database using various distance measures. The results are promising and it shows the LBP feature is biased by the complex background and it affects the performance of the CBIR system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::87ec927965067bb7122c935a30312c16 https://doi.org/10.1007/978-981-13-8676-3_42 Zobrazit plný text záznamu