Image attributes: An investigation

Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Information Science and Technology


Elizabeth Liddy


indexing systems, retrieval, computerization, Information Systems

Subject Categories

Library and Information Science


With the rapid expansion in imaging technologies, access to collections of images is a subject of major interest. Indexing systems and computerized retrieval systems for images both need data concerning those image attributes which are typically described. To date, there has been little research upon which to base choices as to which attributes should be included in access systems for images. This research reviews appropriate literature in the psychology and aesthetics of art, image indexing, and cognitive psychology as a foundation for exploratory research investigating attributes typically described in several types of tasks using pictorial images. Participants performed descriptive, categorizing, and searching tasks, and word and phrase data were subjected to content and statistical analyses. Forty-seven image attributes and twelve higher level attribute classes are described. The data suggest that indexing of literal object is of prime significance, as is indexing of the human form and other human characteristics and associated attributes. The concept of location occurs frequently and needs to be addressed. Color is both typically and consistently described and appears to cue attention to certain attributes or areas as well as providing additional information about these attributes. "Content/Story" and other abstract and affective attributes are also typically described, suggesting that image indexing may benefit by application of concepts associated with indexing of fiction.

The strongest factor affecting the image descriptions is the nature of the specific task. The describing tasks and the Sorting and Concept Search Task produced two markedly different distributions of data. The describing tasks appear to mirror a specific item search, whereas the Sorting and Concept Search Task appear to elicit more of a browsing type of behavior.

Constructs such as Figure-Ground, prototypes, and schemas are discussed as appropriate contexts for decisions concerning indexing of image attributes. Similarity among images cannot be represented solely by perceptual attributes but must take into account interpretive attributes as well. Term variability is less than might have been expected, suggesting some constraints may exist on the process of communicating about visually perceived data. Future research includes replication of the data with other participants and images, and specification and testing of a set of heuristics to guide decisions in describing the content of visual images for a generalized group of users.


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