Wireless Sensor Networks (WSNs) have quite an exceptionally significant effect in diverse fields correlated to surveillance in which coverage plays an essential role. In specific, the coverage holes are actually instigated by both randomized distribution of the wireless sensor nodes and the failure of nodes. Recharging or repairing the battery is difficult, and thus the collaborative identification and estimation of coverage holes and the reclamation of these holes has been considered significant. When organizing the sensor nodes in a large scale WSNs, it is indeed complicated to cover the target or the region of interest (ROI). Coverage quality is compromised by the occurrence of holes in the monitored area of surveillance. This paper proposes a collaborative distributed point location based coverage hole detection methodology to spot coverage holes in an energy efficient manner. Firstly, construct a polygon using a visibility estimation approach on the basis of neighborhood information. Then a point location based hole detection algorithm is used to diagnose whether coverage hole is existing or not in the ROI. Also, the extent of the coverage hole is estimated based on computational geometry based modified partitioning approaches which not only determines the exact region of the hole but also accurately detects the point where the node fails. The accuracy of the algorithm is evaluated here based on statistical proofs. Comparing current coverage hole detection approaches, the output results of the proposed framework surpasses existing algorithms in standings of coverage rate, energy efficiency and network lifetime.