measure the comoving number density of sources.

The paper is organized as follows. In §\[algorithm\] we review the [vtpdetect]{} algorithm and describe the improvements and the additions of [*EXSdetect*]{}. In §\[simu\] we discuss the practical case of the ongoing [*Swift*]{} X-ray Cluster Survey [SXCS, @tundo12], presenting extensive simulations aimed at testing the performance and evaluating the completeness of the survey. In §4 we briefly discuss the effect of improving the angular resolution. Finally, in §\[conclusions\] we summarize our findings.

Algorithm\[algorithm\]
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 VT+FOF as implemented in [vtpdetect]{}\[VTP\]
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There are several ways to find photon density enhancements, and therefore identify source candidates in an X-ray image. The simplest way is to search across the image inside sliding boxes with different sizes and shapes. A more effective option is to search for overdensities on different scales in Fourier space, making use of wavelet transform. Another possibility is to calculate the local flux density across the image in Voronoi cells and locate excess in the flux density distribution. This method has been introduced by @ebeling93 and is implemented in the [ciao]{} task [vtpdetect]{}. This algorithm is a combination of the classical VT and FOF. The classical VT is a nonparametric method that uniquely 