Date Approved


Embargo Period


Document Type


Degree Name

M.S. Electrical and Computer Engineering


Electrical and Computer Engineering


Henry M. Rowan College of Engineering


Ying (Gina) Tang, Ph.D.

Committee Member 1

Li, Jie, Ph.D.

Committee Member 2

Zhu Cheng, Ph.D.


point cloud stitching, iterative closest point, K-nearest neighbor


Three-dimensional modeling; Computer graphics


Electrical and Computer Engineering | Engineering


The basic principle of stitching is joining or merging any two materials or objects. 3D point cloud stitching is basically stitching two 3D point cloud together. 3D point cloud stitching is an emerging topic and there are multiple ways to achieve it. There are various methods for stitching which all have changes throughout the time. The existing methods do have shortcomings and have ignored the multiangle stitching of a same model or an object. This shortfall leads to many deficiencies in the ability of a stitching algorithm to maintain accuracy over the period. In this work I have introduced a new approach for an iterative based approach for 3d multi-angle point cloud stitching using ICP (Iterative closest point algorithm) and KNN (K-nearest neighbor). The design follows an incremental approach to achieve the results. This is a novel approach of stitching multiple 3D point clouds taken from multiple angles of a single bust. The framework is evaluated based on the stitching results provided by the algorithm capability of stitching multiple point cloud into a solid model.