Automated feature measurement for human chromosome image analysis in identifying centromere location and relative length calculation using LabVIEW

Most of the ancestral disorders or naturalistic abnormalities that may be occurring in the succeeding generations can be identified through the analysis of appearance and morphological characteristics of each chromosome. Human Chromosome image analysis comprised of image preprocessing, total variation regularization, segmentation, attributes extraction, and image diagnosis. Karyotyping is the most standard procedure for analyzing and classifying the chromosomes from images of metaphase dispersion. In nonbanding framework, an artifact of the karyogram in which the autosome chromosomes are numbered from 1 to 22 in diminishing order of size and the sex chromosomes are referred as X and Y. In this paper an effective algorithm for automatically locating the centromere and determining the length of the short arm (p_arm) and long arm (q_arm) of the chromosome using LabVIEW is presented. The procedure is based on the edge coordinates profile extraction algorithm of binary image of the chromosome. The gross categorization error rate is decreased by providing the best result in identifying the type of each chromosome based on the exact location of the centromere and the length of two arms.