Comput. Sci. & Inf. Eng., National Taiwan Univ.Liu, Wen-JunWen-JunLiuChen, Bee-ChungBee-ChungChenJIEH HSIANG2007-04-192018-07-052007-04-192018-07-052003-07https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908478741&doi=10.1109%2fICME.2003.1220913&partnerID=40&md5=3d5264689c4455ca2702c6749d70b93fWe propose an image retrieval methodology for a collection of similar images. By similar, we mean that one can define, for the collection, a set of dimensions, and for each of which a set of features. The dimensions are used to capture the essential characteristics of the images in the collection, and the features are for describing each image to a certain degree. We call this strategy fine-grained image retrieval to differentiate it from the more common coarse-grained retrieval, which does not assume any semantic properties on the image collection. The effectiveness of our methodology is demonstrated through an icon-based interactive retrieval system on a collection of butterfly images. This system provides the user with a friendly initial query-by-feature (QBF) interface. The user can then use query-by-example (QBE) to refine the query. In addition to presenting an outline of the methodology and the implementation on butterfly images, we also present some experimental results. © 2003 IEEE.application/pdf319775 bytesapplication/pdfen-USSearch engines; Semantics; Coarse-grained; Essential characteristic; Image collections; Interactive retrieval systems; Query-by-example; Semantic properties; Similar image; Image retrievaljournal article10.1109/ICME.2003.12209132-s2.0-84908478741http://ntur.lib.ntu.edu.tw/bitstream/246246/200704191002952/1/01220913.pdf