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...

A perceptual approach to generating features for use in indexing and retrieving images is described. Salient regions that immediately attract the eye are colour (textured) regions that usually dominate an image. Features derived from these will allow search for images that are similar perceptually. We compute colour features and Gabor colour texture features on regions identified from a coarse ...

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...

A framework for combining object detection techniques with a content-based image retrieval(CBIR) system is discussed. As an example, a special CBIR system which focuses on human faces as foreground and decides the similarity of images based on background features is presented. This system may be useful in automatically generating albums from consumer photos.