موضوع فارسی :طبقه بندی تصویر سونوگرافی در ماشین بردار پشتیبانی مبتنی بر با
دو ویژگی مولفه های مستقل
موضوع انگلیسی :Ultrasonic image classification based on support vector machine with
two independent component features
تعداد صفحه :8
فرمت فایل :PDF
سال انتشار :2011
زبان مقاله : انگلیسی
Imbalance of gender ratio at birth has been a serious phenomenon in China. To solve
this problem, a scheme for ultrasonic image classification is proposed for preventing
fetus gender examination with non-medical purposes. Tens of thousands of ultrasonic
images with and without sexual organs are collected to establish a professional database.
These images are preprocessed firstly by cropping, de-noising and compression. And
then, independent component analysis (ICA) is applied for feature extraction under two
architectures, which give local and global information respectively. The first architecture
treats the images as random variables and the pixels as outcomes, while the second
treats the pixels as random variables and the images as outcomes. After training of
selected samples, a support vector machine (SVM) classifier which combined the two ICA
representations is established for recognition, and a good performance is given for testing
data. Finally, some new technique is suggested for algorithm improvement in the future
