Several approaches have been introduced in image retrieval field. However, many limitations, such as the semantic gap, still exist. As our motivation is to improve image retrieval accuracy, this paper presents an image retrieval system based on visual vocabulary and ontology. We propose, for every query image, to build visual vocabulary and ontology based on images annotations. Image retrieval ...

This paper attempts to discuss the evolution of the retrieval approaches focusing on development, challenges and future direction of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level fea...

This paper deals with the semantic-based web mining for image retrieval by means of enhanced Support Vector Machine (SVM). Generally, conventional Content-Based Image Retrieval (CBIR) systems are unsuccessful to satisfy users’ requirement because of the ‘semantic gap’ among the derived features and the user’s query. A large amount of existing approaches shows certain predetermined semantic cate...

This paper presents a framework for semi-automatic annotation and semantic image retrieval, applied to the sports domain, based upon semantic analysis of both image text captions and visual features of the image. Unstructured text captions of images are analysed in order to extract the concepts and restructure them into a semantic model. SVM classification of the multi-dominant colours and edge...

With increase in number of digital images, retrieval of images efficiently becomes an important topic for research. Traditional methods for image retrieval used metadata associated with images, commonly known as keywords. These methods empowered many World Wide Web search engines and achieved reasonable amount of accuracy. A novel image re-ranking framework propose, which offline learns differe...

This paper presents a method for retrieval of remote sensing images using low dimensional code of the spatial layout of a scene, which is proposed to represent the meaning of the scene. This semantic feature is based on the statistical features of gradient orientations. To capture coarse spatial information, the semantic feature is represented in a pyramidal structure. The level of the pyramid ...

Semantics-based retrieval capability is greatly desirable for large-scale image collections. This paper proposes a novel approach to semantics-based image retrieval and organization using thesaurus, which addresses the representation, acquisition, and utilization of image semantics in a systematic and integrated manner. Firstly, a semantic network is constructed from thesaurus, which represents...

Satellite images play an important role for collection of geographical information. However, the use of such images is limited to a greater extent due to its retrieval complexities. Traditional methods using text have also failed to yield desired and time-saving results. Therefore, Content based image retrieval using high semantic features has been developed to overcome problems related to text...

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by u...