Topic
Contourlet
About: Contourlet is a research topic. Over the lifetime, 3533 publications have been published within this topic receiving 38980 citations.
Papers published on a yearly basis
Papers
More filters
12 May 2008
TL;DR: The problem of recognizing a face from a single sample available in a stored dataset is addressed by using the Fisherface method on a generic dataset and the recognition scheme is extended to multiscale transform domains like wavelet, curvelet and contourlet.
Abstract: The problem of recognizing a face from a single sample available in a stored dataset is addressed. A new method of tackling this problem by using the Fisherface method on a generic dataset is explored. The recognition scheme is also extended to multiscale transform domains like wavelet, curvelet and contourlet. The proposed method in the transform domain shows better recognition errors than the SPCA algorithm and Eigenface selection method, both of which are specially tailored for recognizing faces from single samples.
24 citations
TL;DR: Wang et al. as mentioned in this paper proposed a two-dimensional (2-D) TFPF based on Contourlet transform, which considers spatial correlation and improves the performance of the TFPFs.
24 citations
TL;DR: A spectral resolution enhancement algorithm via the contourlet transforms regularization for FTIR spectral imaging that leads the high-resolution FTIR spectrum as a more efficient tool for the recognition of teacher's facial expressions in the intelligent learning environment.
24 citations
TL;DR: Experimental results show that the proposed method can extract the edge feature accurately and efficiently and improves the edge detection results of GVF Snake model effectively.
24 citations
TL;DR: Experimental results demonstrate that the proposed watermarking scheme preforms better in terms of invisibility and robustness than other related schemes.
Abstract: A blind watermarking algorithm in multiple transform domains is presented for copyright protection. This robust algorithm is designed by fusing contourlet transform (CT), discrete cosine transform (DCT) and singular value decomposition (SVD). The host image is first decomposed by one-level CT and its low frequency sub-band is partitioned into 8 × 8 non-overlapping blocks. Then, each block is transformed by DCT and several middle frequency DCT coefficients with good stability are selected to construct the carrier matrix. Finally, the watermark is embedded by modifying the largest singular values of two carrier matrices. Besides, the geometric distortion factor is estimated with the speed up robust features (SURF) algorithm. The proposed watermarking scheme is evaluated in terms of imperceptibility and robustness. Experimental results demonstrate that the proposed watermarking scheme preforms better in terms of invisibility and robustness than other related schemes.
24 citations