A Digital Image Processing Algorithm for Automation of Human Karyotyping

Abstract

This research work aims to propose and implement a compute efficient application for augmenting the process of paired chromosome alignment called karyotyping. The methodology is a combination of various digital image processing techniques which serves as an effective solution for analyzing and processing raw microscopic images. The different phases for analysis include image acquisition, object segmentation, feature selection and extraction, and finally classification. However, certain open issues need to be tackled such as presence of marker, twisted or overlapped chromosomes. Hence, the consistency of this system relies on image quality and resolution. Manual intervention to some extent accounts for robust identification and classification.