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Surveillance wireless sensor networks are deployed at perimeter or border locations to detect unauthorized intrusions. For deterministic deployment of sensors, the quality of deployment can be determined sufficiently by analysis in advance of deployment. However, when random deployment is required, determining the deployment quality becomes challenging. To assess the quality of sensor deployment, appropriate measures can be employed that reveal the weaknesses in the coverage of SWSNs with respect to the success ratio and time for detecting intruders. In this article, probabilistic sensor models are adopted, and the quality of deployment issue is surveyed and analyzed in terms of novel measures. Furthermore, since the presence of obstacles in the surveillance terrain has a negative impact on previously proposed deployment strategies and analysis techniques, we argue in favor of utilizing image segmentation algorithms by imitating the sensing area as a grayscale image referred to as the iso-sensing graph. Finally, the effect of sensor count on detection ratio and time to detect the target is analyzed through OMNeT++ simulation of an SWSN in a border surveillance scenario.