Multi-level image segmentation and object representation for content based image retrieval

Date

2001-01-26

Author

Duygulu, P
Yarman-Vural, F

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

54
views

0
downloads

Due to the increasing demand and offer of tile technology, the next generation of the image file formats will be more likely to store and retrieve images based oil their semantic content. Thus, an image should be segmented into "meaningful' regions, each of which corresponds to all object and/or background. In this study., we propose a scheme for multi-level image segmentation, based oil a simple descriptor, called "the closest color in the same neighborhood". Tile proposed scheme generates a stack of images without using arty segmentation threshold. The stack of images is hierarchically ordered in a uniformity tree. The uniformity tree is, then, associated with a semantic tree, which is built by tile user for content based representation. The experiments indicate superior results for retrieving images, which consist of fen objects and a background.

Subject Keywords

Content based image retrieval, Multi-level image segmentation, Color descriptor

URI

https://hdl.handle.net/11511/66040

DOI

https://doi.org/10.1117/12.410956

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Design and implementation of a novel visual analysis system for image clasiffication Altintakan, Ümit Lütfü; Yazıcı, Adnan; Körpeoğlu, İbrahim; Department of Computer Engineering (2013) Possibilities offered by the technology to create, share and disseminate image and video data have resulted in a rapid increase in the available visual data. However, the data is useless unless it is effectively accessed, which necessitates the semantic analysis of visual data. In this dissertation, we present a novel visual analysis system along with its application to image classification problem. We aim to address the challenges in the area originated from the semantic gap, and to facilitate the research...
HANOLISTIC: A Hierarchical Automatic Image Annotation System Using Holistic Approach Karadag, Ozge Oztimur; Yarman Vural, Fatoş Tunay (2009-06-25) Automatic image annotation is the process of assigning keywords to digital images depending on the content information. In one sense, it is a mapping from the visual content information to the semantic context information. In this study, we propose a novel approach for automatic image annotation problem, where the annotation is formulated as a multivariate mapping from a set of independent descriptor spaces, representing a whole image, to a set of words, representing class labels. For this purpose, a hierar...
Superpixel based efficient image representation for segmentation and classification Taşlı, Hüseyin Emrah; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2013) The wide availability of visual capture and display devices with increasing resolution and a ordable prices, made the visual data an indispensable part of our life. The enormous amount of visual data produced every day is captured, stored and sometimes processed for further analysis. In this era of technological improvement, where an exponential increase in the number and capability of the devices is experienced, researchers have focused on e cient and accurate ways to reach, store, analyse and display the ...
DATA-DRIVEN IMAGE CAPTIONING WITH META-CLASS BASED RETRIEVAL Kilickaya, Mert; Erdem, Erkut; Erdem, Aykut; İKİZLER CİNBİŞ, NAZLI; Çakıcı, Ruket (2014-04-25) Automatic image captioning, the process cif producing a description for an image, is a very challenging problem which has only recently received interest from the computer vision and natural language processing communities. In this study, we present a novel data-driven image captioning strategy, which, for a given image, finds the most visually similar image in a large dataset of image-caption pairs and transfers its caption as the description of the input image. Our novelty lies in employing a recently' pr...
Geospatial Object Recognition From High Resolution Satellite Imagery Ergul, Mustafa; Alatan, Abdullah Aydın (2013-01-01) In this paper, a novel automatic geo-spatial object recognition algorithm from high resolution satellite imagery is proposed. The proposed algorithm consists of two main steps; the generation of hypothesis with a local feature based algorithm and verification step with a shape based approach. The superiority of this method is the ability of minimization of false alarm number in the recognition and this is because object shape includes more characteristic and discriminative information about object identity ...

Citation Formats

P. Duygulu and F. Yarman-Vural, “Multi-level image segmentation and object representation for content based image retrieval,” 2001, vol. 4315, p. 460, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66040.