  The structure of interstellar medium can be characterised at large scales in
terms of its global statistics (e.g. power spectra) and at small scales by the
properties of individual cores. Interest has been increasing in structures at
intermediate scales, resulting in a number of methods being developed for the
analysis of filamentary structures. We describe the application of the generic
template-matching (TM) method to the analysis of maps. Our aim is to show that
it provides a fast and still relatively robust way to identify elongated
structures or other image features. We present the implementation of a TM
algorithm for map analysis. The results are compared against rolling Hough
transform (RHT), one of the methods previously used to identify filamentary
structures. We illustrate the method by applying it to Herschel surface
brightness data. The performance of the TM method is found to be comparable to
that of RHT but TM appears to be more robust regarding the input parameters,
for example, those related to the selected spatial scales. Small modifications
of TM enable one to target structures at different size and intensity levels.
In addition to elongated features, we demonstrate the possibility of using TM
to also identify other types of structures. The TM method is a viable tool for
data quality control, exploratory data analysis, and even quantitative analysis
of structures in image data.
