Title :
Automatic Analysis of High-Resolution G Bands of Triticum Monococcum Chromosomes Based on the MBNN
Author :
Cai, Nian ; Pan, Qing ; Hu, Kuanghu ; Xiong, Haitao
Author_Institution :
Guangzhou Higher Educ. Mega Center, Guangdong Univ. of Technol., Guangzhou
Abstract :
A method based on the model based neural network (MBNN) is proposed to automatically analyze high-resolution G bands of Triticum monococcum chromosomes. The MBNN-3P is employed to segmented the G-band images. Then five features of chromosomes are extracted from the segmented images. At last, the features are input into the MBNN for classification. The results indicate that the method provides a significant way for the automatic analysis of high-resolution G bands of plant chromosomes accurately.
Keywords :
biological techniques; biology computing; botany; cellular biophysics; feature extraction; genetics; image classification; image resolution; image segmentation; neural nets; G-band image segmentation; automatic high-resolution G band analysis; feature extraction; image classification; model-based neural network; triticum monococcum chromosome; Automation; Biological cells; Biophysics; Chaos; Educational technology; Feature extraction; Genetics; Image segmentation; Information analysis; Neural networks; G bands; MBNN; Triticum monococcum chromosomes; automatica analysis;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.632
