Journal of Intelligent Information Systems

, Volume 39, Issue 3, pp 651-685

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Image auto-annotation with automatic selection of the annotation length

  • Oskar MaierAffiliated withInstitute of Informatics, Wrocław University of Technology Email author 
  • , Halina KwasnickaAffiliated withInstitute of Informatics, Wrocław University of Technology
  • , Michal StanekAffiliated withInstitute of Informatics, Wrocław University of Technology


Developing a satisfactory and effective method for auto-annotating images that works under general conditions is a challenging task. The advantages of such a system would be manifold: it can be used to annotate existing, large databases of images, rendering them accessible to text search engines; or it can be used as core for image retrieval based on a query image’s visual content. Manual annotation of images is a difficult, tedious and time consuming task. Furthermore, manual annotations tend to show great inter-person variance: considering an image, the opinions about what elements are significant and deserve an annotation vary strongly. The latter poses a problem for the evaluation of an automatic method, as an annotation’s correctness is greatly subjective. In this paper we present an automatic method for annotating images, which addresses one of the existing methods’ major limitation, namely a fixed annotation length. The proposed method, PATSI, automatically chooses the resulting annotation’s length for each query image. It is held as simple as possible and a build-in parameter optimization procedure renders PATSI de-facto parameter free. Finally, PATSI is evaluated on standard datasets, outperforming various state-of-the-art methods.


Image auto-annotation Variable annotation length Parameter optimization Image similarity