Fuzzy Neighbor Voting for Automatic Image Annotation

Authors

  • Farzin Yaghmaee Department of Electrical and Computer Engineering, Semnan University, Semnan, Iran
  • Vafa Maihami Department of Electrical and Computer Engineering, Semnan University, Semnan, Iran
Abstract:

With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper, we propose a novel image annotation algorithm based on neighbor voting which uses fuzzy system. The performance of the model depends on selecting the right neighbors and a fuzzy system with the right combination of features it offers.Experimental results on Corel5k and IAPR TC12 benchmark annotated datasets, demonstrate that using the proposed method leads to good performance.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

fuzzy neighbor voting for automatic image annotation

with quick development of digital images and the availability of imaging tools, massive amounts of images are created. therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. automatic image annotation (aia) or refers to attaching words, keywords or comments to an image or to a selected part of it. in this paper,...

full text

Automatic Image Annotation for Semantic Image Retrieval

This paper addresses the challenge of automatic annotation of images for semantic image retrieval. In this research, we aim to identify visual features that are suitable for semantic annotation tasks. We propose an image classification system that combines MPEG-7 visual descriptors and support vector machines. The system is applied to annotate cityscape and landscape images. For this task, our ...

full text

Automatic image annotation refinement using fuzzy inference algorithms

Facilitating tasks such as image search is one of the goals of image annotation methods that automatically assign keywords to images. In order to achieve as accurate annotation on object level as possible, and to reduce negative influence of misclassified objects on the inference of scenes, a knowledge based refinement of object classification results is proposed. A fuzzy knowledge representati...

full text

Semi-Automatic Image Annotation

A novel approach to semi-automatically and progressively annotating images with keywords is presented. The progressive annotation process is embedded in the course of integrated keyword-based and content-based image retrieval and user feedback. When the user submits a keyword query and then provides relevance feedback, the search keywords are automatically added to the images that receive posit...

full text

Tags Re-ranking Using Multi-level Features in Automatic Image Annotation

Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 4  issue 1

pages  1- 8

publication date 2016-11-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023