Colour-Texture Image Segmentation using Hypercomplex Gabor Analysis

Bioinformatics and genomic signal processing use computational techniques to solve various biological problems. They aim to study the information allied with genetic materials such as the deoxyribonucleic acid (DNA), the ribonucleic acid (RNA), and the proteins. Fast and precise identification of the protein coding regions in DNA sequence is one of the most important tasks in analysis. Existing digital signal processing (DSP) methods provide less accurate and computationally complex solution with greater background noise. Hence, improvements in accuracy, computational complexity, and reduction in background noise are essential in identification of the protein coding regions in the DNA sequences. In this paper, a new DSP based method is introduced to detect the protein coding regions in DNA sequences. Here, the DNA sequences are converted into numeric sequences using electron ion interaction potential (EIIP) representation. Then discrete wavelet transformation is taken. Absolute value of the energy is found followed by proper threshold. The test is conducted using the data bases available in the National Centre for Biotechnology Information (NCBI) site. The comparative analysis is done and it ensures the efficiency of the proposed system.

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Colour-Texture Image Segmentation using Hypercomplex Gabor Analysis

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Cited by 6 publications

References 13 publications

Applying 3D texture algorithms on MRI to evaluate quality traits of loin

Applying 3D texture algorithms on MRI to evaluate quality traits of loin

A novel method of straight-lines detection based on Hypercomplex Steerable Filters

Improved Algorithm for Analysis of DNA Sequences Using Multiresolution Transformation

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