JRA/objective1/task1

Task 1: Automatic processing (segmentation) of digital images

Research and develop edge detection technology to locate and classify multiple regions of interest within images of NH specimens. Using the principle that pixels in a segment are similar with respect to some characteristic or computed property (e.g. colour, intensity, or texture), develop a method to semi-automatically detect, crop and classify these regions of interest such that they can be subject to appropriate additional processing.

Subtask 1: Development of software for identifying, and potentially cropping, single specimens in a multi-specimen item

The Deliverable for Task 1.1 resulted in Inselect, a desktop software 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. Inselect was developed by the Natural History Museum, London (NHM) and was publicly released in September 2014.

Since its release Inselect has been in almost continual development, testing and refinement. In the current reporting period more than 18 major Inselect issues (both bug fixes and new features) have been closed since September 2015 (a complete list is at https://github.com/NaturalHistoryMuseum/inselect/issues?q=is%3Aissue closed%3A2015-09-01..2016-09-01). A major output was the launch of a new website for Inselect, which provides greatly improved user documentation and a gallery of examples.

Subtask 2: Review of tools to select regions of interest in individual specimens to identify different labels, particularly to help with Task 1.2.

This will investigate identifying regions of interest in preparation of images for OCR, to feed into Task 1.2 and Obj. 3.

Participants: Jörg Holetschek (BGBM), Elspeth Haston (RBGE), Sarah Phillips (RBGK)

Aims of Subtask

1. To enable categorisation of sheets by collectors, country etc to make workflows more efficient

2. To find the most suitable and effective image viewers for a user interface