Academic Research Experience

Antibandwidth Problem for Caterpillars:

My thesis topic was "Antibandwidth problem for the Itchy caterpillars". Antibandwidth problem is an optimaztion problem which consists of placing the vertices of a graph on a line in consecutive integer points in such a way that the minimum difference of adjacent vertices is maximized. The problem was originally introduced like

dual variation of well-known bandwidth problem, but it can be reinterpreted in many ways as special multiprocessor scheduling problem, special linear layout

problem or variant of obnoxious facility location problem. The antibandwidth problem is NP-complete. However there are very few exact results for nontrivial

graph classes and some classes of graphs where time for finding the parameter is polynomially bounded.In our thesis, we study the known results of the antibandwidth problem and provide and alternate solution of a special class of tree that we call ”Itchy Caterpillar”. We give a linear time algorithm and the bound of the antibandwidth for itchy caterpillar which is tight.

My thesis paper: View, A copy of my thesis paper will be found in the bottom of the page.

Thesis Presentation: View

A shorter version of our work has been accepted to the Workshop on Graph Drawing and Graph Algorithms. The shorter version can be found on the download section. You can view it from here

Content Based Image Retrieval:

To implement the project in pattern recognition coursework I have studied about Content Based Image Retrieval. I have studied several procedures to retrieve image based on its content. But i choose to use neural network to classify the object images. The images for classification are object images that can be divided into foreground and background. To deal with the object images efficiently, in the pre processing step t the object region was extracted using a region segmentation technique. Features for the classification are shape-based texture features extracted from wavelet-transformed images. The neural network classifiers constructed for the features using the back-propagation learning algorithm. Among the various texture features, the diagonal moment was the most effective.

Presentation: view