A New Content-Based Image Indexing and Retrieval System of Mosaic Images

Mhedhbi, Meriem; Mezhoud, R.; M'Hiri, Slim; Ghorbel, Faouzi

doi:10.1109/ictta.2006.1684644

Cited by 10 publications

(6 citation statements)

References 8 publications

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“…M'hedhbi et al [16] use a CBIR approach to retrieve mosaics based on shape descriptors. The aim is to dedicate a recognition system to archaeologists.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, some researchers have tackled the problem of indexing and cataloging images of mosaics with all the challenges such image particularities present [15][16][17]. M'hedhbi et al [16] use a CBIR approach to retrieve mosaics based on shape descriptors.…”

Section: Introductionmentioning

confidence: 99%

“…They use a robust MPEG7 of low level shape descriptors to index objects. Those retrieval systems [1,2,7,8,[10][11][12][13][14][15][16][17] use, mainly, low level features and don't give the possibility to specify multiple objects in the user query. Nevertheless, a few multi-objects based image indexing and retrieval systems have been developed [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

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An Intelligent mutli-object retrieval system for historical mosaics

Maghrebi¹,

Ammar²,

Alimi³

et al. 2013

IJACSA

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Abstract-In this work we present a Mosaics Intelligent Retrieval System (MIRS) for digital museums. The objective of this work is to attain a semantic interpretation of images of historical mosaics. We use the fuzzy logic techniques and semantic similarity measure to extract knowledge from the images for multi-object indexing. The extracted knowledge provides the users (experts and laypersons) with an intuitive way to describe and to query the images in the database. Our contribution in this paper is firstly, to define semantic fuzzy linguistic terms to encode the object position and the inter-objects spatial relationships in the mosaic image. Secondly, to present a fuzzy color quantization approach using the human perceptual HSV color space and finally, to classify semantically the mosaics images using a semantic similarity measure. The automatically extracted knowledge are collected and traduced into XML language to create mosaics metadata. This system uses a simple Graphic User Interface (GUI) in natural language and applies the classification approach both on the mosaics images database and on user queries, to limit images classes in the retrieval process. MIRS is tested on images from the exceptional Tunisian collection of complex mosaics. Experimental results are based on queries of various complexities which yielded a system's recall and precision rates of 86.6% and 87.1%, respectively, while the classification approach gives an average success rate evaluated to 76%.

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“…M'hedhbi et al [16] use a CBIR approach to retrieve mosaics based on shape descriptors. The aim is to dedicate a recognition system to archaeologists.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Intelligent mutli-object retrieval system for historical mosaics

Maghrebi¹,

Ammar²,

Alimi³

et al. 2013

IJACSA

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show abstract

“…[1] for an overview of digital mosaic frameworks and references cited therein). A first attempt to propose a contentbased and image retrieval system dedicated to ancient mosaic images has been presented in [2]. In this work, efforts have been focused on pattern recognition aspects, by using an invariant description of semantic objects present in scenes using Fourier-Mellin transform [3,4].…”

Section: Introductionmentioning

confidence: 99%

Tessella-oriented segmentation and guidelines estimation of ancient mosaic images

Benyoussef

Derrode

2008

J. Electron. Imaging

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“…These treasures are carefully photographed and catalogued in such a way to be at the reach of researchers, thus avoiding direct handling of such fragile items. Some researchers have recently tackled the problem of indexing and cataloguing mosaic-related images with all the challenges such image peculiarities could present (Stanco et al [7], M'hedbi et al [8], Maghrebi et al [9]). In this respect, M'hedbi et al [7] use a CBIR (Content Based Information Retrieval) approach, whereby to retrieve mosaics based on shape descriptors, while Maghrebi et al [9] present a retrieval system of Roman-mosaic images using drawing queries, involving a robust MPEG7 shape descriptors to index objects.…”

Section: Introductionmentioning

confidence: 99%

FMIRS: A Fuzzy indexing and retrieval system of mosaic-image database

Maghrebi

2014

ELCVIA

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This work is dedicated to present a fuzzy-set based system useful for image indexing and retrieval pertaining to historical Roman-mosaics. This exceptional collection of mosaics dates back from the first to fourth centuries AD. Considering the state of these images (i.e. noise, color degradation, etc.) a fuzzy features definition is necessary. Thereby, we use a robust to rotation, scale and translation fuzzy extended curvature scale space (CSS) as shape descriptor. Furthermore, we propose a fuzzy color-quantization approach, applied on mosaics, using HSV color space. The system allows for two user-friendly querying modes: a drawing based mode and the mode that fusion both shape and color features using a unified fuzzy similarity measure. Based on queries of variable complexity, the advanced fuzzy system has managed to achieve interesting recall, precision and F-measure rates.

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A New Content-Based Image Indexing and Retrieval System of Mosaic Images

Cited by 10 publications

References 8 publications

An Intelligent mutli-object retrieval system for historical mosaics

An Intelligent mutli-object retrieval system for historical mosaics

Tessella-oriented segmentation and guidelines estimation of ancient mosaic images

FMIRS: A Fuzzy indexing and retrieval system of mosaic-image database

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