Visible to the public A THz Image Edge Detection Method Based on Wavelet and Neural Network

TitleA THz Image Edge Detection Method Based on Wavelet and Neural Network
Publication TypeConference Paper
Year of Publication2009
AuthorsWang, R., Li, L., Hong, W., Yang, N.
Conference Name2009 Ninth International Conference on Hybrid Intelligent Systems
Date PublishedAug. 2009
PublisherIEEE
ISBN Number978-0-7695-3745-0
KeywordsCanny operator method, composability, edge detection, edge image fusion, Electromagnetic radiation, frequency, Image analysis, Image edge detection, image fusion, image processing, image recognition, Information security, low-frequency subimage detection, Metrics, neural nets, Neural Network, neural network method, Neural networks, Pattern recognition, pubcrawl, resilience, Resiliency, Scalability, security, terahertz wave imaging, terahertz waves, THz image edge detection method, wavelet, wavelet analysis, wavelet decomposition, wavelet transform method, wavelet transforms
Abstract

A THz image edge detection approach based on wavelet and neural network is proposed in this paper. First, the source image is decomposed by wavelet, the edges in the low-frequency sub-image are detected using neural network method and the edges in the high-frequency sub-images are detected using wavelet transform method on the coarsest level of the wavelet decomposition, the two edge images are fused according to some fusion rules to obtain the edge image of this level, it then is projected to the next level. Afterwards the final edge image of L-1 level is got according to some fusion rule. This process is repeated until reaching the 0 level thus to get the final integrated and clear edge image. The experimental results show that our approach based on fusion technique is superior to Canny operator method and wavelet transform method alone.

URLhttps://ieeexplore.ieee.org/document/5254609
DOI10.1109/HIS.2009.298
Citation Keywang_thz_2009