Title :
A Novel Medical Image Feature Extraction Algorithm
Author :
Zhang, Qidong ; Gao, Liqun
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
Abstract :
A new algorithm to combine the advantages of both canny operator and the nonsubsampled contour let transform for medical image feature extraction is proposed. Canny operator is the optimum edge detection module. The nonsubsampled contour let transform has the properties of multi-scale and multi-direction. Firstly, the canny operator is used to detect the edges of image, and then the edge image is decomposed with the nonsubsampled contour let transform. The geometry moments of the nonsubsampled contour let coefficient with different scales and directions are obtained as the features of image. Similarity measurement is implemented by using euclidean distance between the features of query image and that of each image in the image database. Meanwhile its effectiveness is compared with the method of retrieval based wavelet transform. A database of medical images was retrieved by this method. The result shows that this method has good performance.
Keywords :
edge detection; feature extraction; geometry; image retrieval; medical administrative data processing; medical image processing; visual databases; wavelet transforms; canny operator; edge image decomposition; euclidean distance; geometry moments; image database; medical image feature extraction; medical image retrieval; new algorithm; nonsubsampled contourlet transform; optimum edge detection module; query image; retrieval based wavelet transform; Nonsubsampled contourlet transform; canny operator; geometry moments;
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-8548-2
Electronic_ISBN :
978-0-7695-4249-2
DOI :
10.1109/ICINIS.2010.172