Detection of structural variations is an important problem. With the next generation sequencing technology, it is relatively easier to obtain a set of paired-end short reads from an individual (the donor). By aligning these reads onto a reference genome (the reference), we are able to detect some of the structural variations that exist between the donor and the reference. A number of tools were developed in this direction. However, these tools are not able to detect all types of variations. In particular, they do not perform well for the detection of tandem duplications which are found to be associated with some diseases. In this paper, we try to solve this problem and developed algorithm to identify novel tandem duplications that exist in donor and vice versa. Experimental results on both simulated and real datasets showed that our solutions are effective.