scholarly journals On Image Retrieval Using Salient Regions with Vector-Spaces and Latent Semantics

2005 ◽  
pp. 540-549 ◽  
Author(s):  
Jonathon S. Hare ◽  
Paul H. Lewis
Keyword(s):  
Image Retrieval ◽  
Vector Spaces ◽  
Salient Regions

EXTRACTING SALIENT REGIONS AND LEARNING IMPORTANCE SCORES IN REGION-BASED IMAGE RETRIEVAL

2003 ◽  
Vol 17 (08) ◽  
pp. 1349-1367 ◽  
Author(s):  
BYOUNGCHUL KO ◽  
HYERAN BYUN
Keyword(s):  
Image Retrieval ◽  
Relevance Feedback ◽  
Retrieval System ◽  
Retrieval Performance ◽  
Matching Process ◽  
Similar Images ◽  
Salient Regions ◽  
Feedback Method ◽  
Successful Retrieval ◽  
Feedback Algorithm

In this paper, we propose a new method for extracting salient regions and learning their importance scores in region-based image retrieval. In Region-Based Image Retrieval (RBIR), not all the regions are important for retrieving similar images and rather, in retrieval, the user is often interested in performing a query on only one or a few regions rather than the whole image. Therefore, for a successful retrieval system, it is an important issue to specify which regions are important for retrieving an image. To extract salient regions from images automatically, we make three assumptions and determine salient regions with their importance scores. In this paper, we apply the relevance feedback algorithm to the matching process as two different purposes: one is for updating importance scores of salient regions and the other is for updating weights of feature vectors. By using our relevance feedback method, the matching process can improve retrieval performance interactively and allow progressive refinement of query results according to the user's feedback action. Through experiments and comparison with other methods, our proposed method shows good performance as well as easy and semantic interface for region-based image retrieval. The efficacy of our method is validated using a set of 3000 images from Corel-photo CD.

Image retrieval using wavelet-based salient regions

2011 ◽  
Vol 59 (4) ◽  
pp. 219-231 ◽  
Author(s):  
M W Jian ◽  
J Y Dong ◽  
J Ma
Keyword(s):  
Image Retrieval ◽  
Salient Regions

A novel remote sensing image retrieval method based on visual salient point features

Sensor Review ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 349-359 ◽  
Author(s):  
Xing Wang ◽  
Zhenfeng Shao ◽  
Xiran Zhou ◽  
Jun Liu
Keyword(s):  
Remote Sensing ◽  
Image Retrieval ◽  
Remote Sensing Image ◽  
Saliency Map ◽  
Visual Features ◽  
Salient Point ◽  
Remote Sensing Images ◽  
Retrieval Method ◽  
Content Type ◽  
Salient Regions

Purpose – This paper aims to present a novel feature design that is able to precisely describe salient objects in images. With the development of space survey, sensor and information acquisition technologies, more complex objects appear in high-resolution remote sensing images. Traditional visual features are no longer precise enough to describe the images. Design/methodology/approach – A novel remote sensing image retrieval method based on VSP (visual salient point) features is proposed in this paper. A key point detector and descriptor are used to extract the critical features and their descriptors in remote sensing images. A visual attention model is adopted to calculate the saliency map of the images, separating the salient regions from the background in the images. The key points in the salient regions are then extracted and defined as VSPs. The VSP features can then be constructed. The similarity between images is measured using the VSP features. Findings – According to the experiment results, compared with traditional visual features, VSP features are more precise and stable in representing diverse remote sensing images. The proposed method performs better than the traditional methods in image retrieval precision. Originality/value – This paper presents a novel remote sensing image retrieval method based on VSP features.

Sign in / Sign up

Export Citation Format

Share Document