Inselect is a desktop application that automates the cropping of individual images of specimens from whole-drawer scans and similar images that are generated by digitisation of museum collections. It combines image processing, barcode reading, validation of user-defined metadata and batch processing to offer a high level of automation. Inselect runs on Windows and Mac OS X and is open-source.

The problem

Natural history collections are vast and varied and present many substantial challenges to digitisation. At the Natural History Museum, London, for example, there are an estimated 33 million insect specimens, housed in 130 thousand drawers:

Drawers of pinned beetles at Natural History Museum, London

It is a lot easier and quicker to image 130 thousand drawers rather than 33 million individual insects. However, by themselves drawer-level images are not very useful. Manually cropping each image takes too much time and without unique identifiers the individual images are of questionable value.

The challenge is to efficiently get a single image of each object along with its associated metadata.

How Inselect helps

Inselect aims to solve many of the problems associated with whole-drawer imaging including

  • identifying individual specimens, along with any associated labels,
  • placing a bounding box around each,
  • cropping out specimen-level images,
  • capturing metadata such as catalogue numbers, location within the collection, and possibly information on labels and
  • associating metadata with the cropped images.


This research received support from the SYNTHESYS Project, which is financed by European Community Research Infrastructure Action under the FP7 Integrating Activities Programme (Grant agreement number 312253), and from the U.K. Natural Environment Research Council.