A novel algorithm for straightening highly curved images of human chromosome

An effective chromosome image processing algorithm for straightening highly curved chromosomes is presented. This will extend the domain of application of most of the previously reported algorithms to the curved chromosomes. The proposed algorithm is based on the calculating and analyzing the vertical and horizontal projection vectors of the binary image of the chromosome obtained at various rotation angles. The binary image is obtained by thresholding the input image after histogram modification. By minimizing a rotation score S which is defined based on the relative amplitude of the main peaks in the horizontal projections of the rotated pictures, the most appropriately rotated image is identified. This picture is used to determine the bending axis and from which the bending centre of the chromosome, which is then used to artificially straighten the curved chromosome. When applied to the real images of highly curved chromosomes the proposed algorithm could straighten all of the chromosome images within the dataset. To assess the effectiveness of the proposed algorithm, the automatically extracted bending centers are compared to the manually defined ones on the whole data set. Moreover, the density profiles of the chromosomes (a one-dimensional vector obtained by intensity sampling of the chromosome along its longitudinal axis), which is the most important and most commonly used feature for classification purposes, are identified and compared before and after chromosome straightening. The quantitative analysis of the results in both cases showed a close correlation between the two. 2008 Elsevier B.V. All rights reserved.