Texture is widely used in CBIR, and there have been a number of studies over the years to establish which features are perceptually significant. However, it is still diSJicult to retrieve reliably images that the human user would agree are “similar”. This paper reviews a range of computational methods, and compares their performance in class@ing and retrieving imagesporn the Brodatz set. Their ...

We describe the outcome of an effort to understand the behavior of content-based image retrieval (CBIR) technology by examining the behavior of a CBIR system in response to carefully constructed input query images. This work is preliminary and only considers a single CBIR system, SIMPLIcity[4]. We chose this particular system for expediency. It is our intention to develop a methodology suitable...

To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images into semantic categories based on trained pattern classifiers have become active research trends. In this paper, we present dual cascading learning frameworks that extract and combine intraimage and inter-class semant...

One of the challenges in image and video retrieval is the content-based retrieval of images and videos in the web. Less work has been done in this area, mainly due to scalability issues. For this reason, in this paper we investigate this problem by presenting tools for the characterization of the visual contents on specific web collections and a strategy for the search of faces in the web using...

This paper presents an application of perceptual grouping rules for content-based image retrieval. The semantic interrelationships between different primitive image features are exploited by perceptual grouping to detect the presence of manmade structures. A methodology based on these principles in a Bayesian framework for the retrieval of building images, and the results obtained are presented...

The ImageCLEF Photo Retrieval Task 2009 focused on image retrieval and diversity. A new collection was utilised in this task consisting of approximately half a million images with English annotations. Queries were based on analysing search query logs and two different types were released: one containing information about image clusters; the other without. A total of 19 participants submitted 84...

296-220 Abstract In this paper we present a study of the comparison of the performance of content-based image retrieval systems based on structure [1] with those based on histogram and texture analysis methods, where retrieval is concerned with locating images containing manmade objects. The advantage of using structure in such queries is demonstrated by analyzing an image database containing m...

In this paper we analyze the image retrieval problem in presence of possible foreground disturbances. The foreground may be irrelevant for the retrieval but it occludes the background and hence reduces the retrieval accuracy. We propose the use of a video as a query so that the moving foreground can be extracted. The segmented foreground region is subsequently filled into increase the retrieval...