The availability of images in electronic format has resulted in large number of digitalrnimages being used for different applications. The growth in the usage and availability ofrndigital images calls for an efficient means of image data management. This has led to therndevelopment of content based image retrieval (CBIR) systems, which uses visualrncontents of an image such as color, texture or shape for querying image databases. CBIRrnis well researched and there are a large number of image retrieval systems based on thisrntechnology.rnImage retrieval matching can be performed using global features of the whole image (asrnin CBIR), but a comparison that considers part(s) of images for similarity-based retrievalrnis sometimes a more natural approach. Regions of an image that are of particular interestrnto humans are termed salient-objects of an image. Salient â€“object based image retrieval isrnnot well researched, but there some developed system that model the salient object of thernimage using a Minimum Bounding Rectangle. In this work a new approach is proposedrnwhich considers the natural shape of the salient objects contained within an image. AnrnImage segmentation tool is used to automatically identify salient objects of an image andrnstore them in an object relational DBMS for multi-criteria image query (query based onrnboth image content, positional predicates and metadata). Furthermore, some techniquesrnhave been proposed in this work to make the image retrieval system accessible within arnpervasive computing environment.rnKeywords: Salient-Object Based Image Retrieval, Image Database, Image Retrieval inrnPervasive Environment, Image Segmentation, Multi-Criteria Image Query.