Automatic Image Annotation based on Dense Weighted Regional Graph
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 3
Abstract
Automatic image annotation refers to create text labels in accordance with images' context automatically. Although, numerous studies have been conducted in this area for the past decade, existence of multiple labels and semantic gap between these labels and visual low-level features reduced its performance accuracy. In this paper, we suggested an annotation method, based on dense weighted regional graph. In this method, clustering areas was done by forming a dense regional graph of area classification based on strong fuzzy feature vector in images with great precision, as by weighting edges in the graph, less important areas are removed over time and thus semantic gap between low-level features of image and human interpretation of high-level concepts reduces much more. To evaluate the proposed method, COREL database, with 5,000 samples have been used. The results of the images in this database, show acceptable performance of the proposed method in comparison to other methods.
Authors and Affiliations
Masoumeh Boorjandi, Zahra Rahmani Ghobadi, Hassan Rashidi
Keywords
Related Articles
- EP ID EP250875
- DOI 10.14569/IJACSA.2017.080346
- Views 124
- Downloads 0
The Visual Web User Interface Design in Augmented Reality Technology
Upon the popularity of 3C devices, the visual creatures are all around us, such the online game, touch pad, video and animation. Therefore, the text-based web page will no longer satisfy users. With the popularity of web...
The Design and Evaluation of a User-Centric Information Security Risk Assessment and Response Framework
The risk of sensitive information disclosure and modification through the use of online services has increased considerably and may result in significant damage. As the management and assessment of such risks is a well-k...
Feasibility of automated detection of HONcode conformity for health-related websites
In this paper, authors evaluate machine learning algorithms to detect the trustworthiness of a website according to HONcode criteria of conduct (detailed in paper). To derive a baseline, we evaluated a Naive Bayes algori...
A Review on Scream Classification for Situation Understanding
: In our living environment, a non-speech audio signal provides a significant evidence for situation awareness. It also compliments the information obtained from a video signal. In non-speech audio signals, screaming is...
Framework Utilizing Machine Learning to Facilitate Gait Analysis as an Indicator of Vascular Dementia
Vascular dementia (VD), the second most common type of dementia, effects approximately 13.9 per cent of people over the age of 71 in the United States alone. 26% of individuals develop VD after being diagnosed with conge...