Next Article in Journal
Group Buying-Based Data Transmission in Flying Ad-Hoc Networks: A Coalition Game Approach
Next Article in Special Issue
Evaluating User Behaviour in a Cooperative Environment
Previous Article in Journal
What Smart Campuses Can Teach Us about Smart Cities: User Experiences and Open Data
Previous Article in Special Issue
Aspect Term Extraction Based on MFE-CRF
Article Menu

Export Article

Open AccessArticle
Information 2018, 9(10), 252;

Integration of Context Information through Probabilistic Ontological Knowledge into Image Classification

Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
Author to whom correspondence should be addressed.
Received: 26 August 2018 / Revised: 21 September 2018 / Accepted: 9 October 2018 / Published: 12 October 2018
(This article belongs to the Special Issue Advanced Learning Methods for Complex Data)
Full-Text   |   PDF [3467 KB, uploaded 12 October 2018]   |  


The use of ontological knowledge to improve classification results is a promising line of research. The availability of a probabilistic ontology raises the possibility of combining the probabilities coming from the ontology with the ones produced by a multi-class classifier that detects particular objects in an image. This combination not only provides the relations existing between the different segments, but can also improve the classification accuracy. In fact, it is known that the contextual information can often give information that suggests the correct class. This paper proposes a possible model that implements this integration, and the experimental assessment shows the effectiveness of the integration, especially when the classifier’s accuracy is relatively low. To assess the performance of the proposed model, we designed and implemented a simulated classifier that allows a priori decisions of its performance with sufficient precision. View Full-Text
Keywords: image object recognition; probabilistic ontology; probabilistic model image object recognition; probabilistic ontology; probabilistic model

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Apicella, A.; Corazza, A.; Isgrò, F.; Vettigli, G. Integration of Context Information through Probabilistic Ontological Knowledge into Image Classification. Information 2018, 9, 252.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Information EISSN 2078-2489 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top