The Semantics of Image Annotation

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,...

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...

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models

Scalable Image Annotation by Summarizing Training Samples into Labeled Prototypes

By increasing the number of images, it is essential to provide fast search methods and intelligent filtering of images. To handle images in large datasets, some relevant tags are assigned to each image to for describing its content. Automatic Image Annotation (AIA) aims to automatically assign a group of keywords to an image based on visual content of the image. AIA frameworks have two main sta...

Meaningfulness of Religious Language in the Light of Conceptual Metaphorical Use of Image Schema: A Cognitive Semantic Approach

According to modern religious studies, religions are rooted in certain metaphorical representations, so they are metaphorical in nature. This article aims to show, first, how conceptual metaphors employ image schemas to make our language meaningful, and then to assert that image-schematic structure of religious expressions, by which religious metaphors conceptualize abstract meanings, is the ba...

Visual Concept Detection using MOD Salient Points

Visual concept detection is the automated detection of image semantics. Detecting image semantics is particularly useful in content based retrieval because it allows us to annotate media with semantically meaningful information. One computationally efficient approach toward subimage annotation is to focus on regions which are considered salient. The novel contribution in this paper is using the...