Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The most widely used cytogenetic method is G-banded karyotyping. A new feature extraction method is proposed for G-banded chromosome recognition. Chromosome features are mostly extracted on chromosome skeleton. The main innovation of the proposed method is extracting features around chromosome boundary contours, not the skeleton. The circular boundary contour signatures are extracted and applied to Discrete Fourier Transformation to get contour descriptor vector. Some chromoseme geometric features are added to this descriptor vector to form the main feature vector. These feature vectors are applied to different classfiers as input and the performances are compared with skeleton based techniques. Experiments show that the proposed method outperforms skeleton based methods dramatically.
['Shahriar Asta', 'Muhammet S. Beratoglu', 'Abdulkerim Çapar']
I am writing a research paper on a idea A boundary based feature extraction method for G-banded chromosome classification
[{"from": "human", "value": "I am writing a research paper on a idea A boundary based feature extraction method for G-banded chromosome classification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The most widely used cytogenetic method is G-banded karyotyping. A new feature extraction method is proposed for G-banded chromosome recognition. Chromosome features are mostly extracted on chromosome skeleton. The main innovation of the proposed method is extracting features around chromosome boundary contours, not the skeleton. The circular boundary contour signatures are extracted and applied to Discrete Fourier Transformation to get contour descriptor vector. Some chromoseme geometric features are added to this descriptor vector to form the main feature vector. These feature vectors are applied to different classfiers as input and the performances are compared with skeleton based techniques. Experiments show that the proposed method outperforms skeleton based methods dramatically."}]