Zhengli Zhu

Pavement Cracks Detection Based on FDWT

Automatic detection of road cracks has been a hot topic since it reduces economic loses. It is not easy to get efficient detection algorithms because of complexity, diversity of pavement images and pavement distresss weak information. In this paper, a new approach of pavement cracks detection based on FDWT (fractional differential and wavelet transform) is proposed. Fractional differential can effectively enhance high-frequency, medium-frequency signals and non-linearly preserve low-frequency signals. After fractional differential covering module is constructed and applied to road images, pavement crack reinforcement is implemented even if the crack is weak signal in smooth area. Then in order to filter noise, wavelet transform is carried out. This approach can reinforce availably pavement images and get better effect especial for weak crack information in smooth area. Experimental results proved that the proposed detection was a valid method for the different road crack image even if there is any noise

Research on Similarity Measurement for Texture Image Retrieval

A complete texture image retrieval system includes two techniques: texture feature extraction and similarity measurement. Specifically, similarity measurement is a key problem for texture image retrieval study. In this paper, we present an effective similarity measurement formula. The MIT vision texture database, the Brodatz texture database, and the Outex texture database were used to verify the retrieval performance of the proposed similarity measurement method. Dual-tree complex wavelet transform and nonsubsampled contourlet transform were used to extract texture features. Experimental results show that the proposed similarity measurement method achieves better retrieval performance than some existing similarity measurement methods.

Semisubsampled Wavelet Transform Based Image Watermarking with Strong Robustness to Rotation Attacks

In this paper, we develop a novel transform called semisubsampled wavelet transform (SSWT) and employ it to image watermarking. SSWT consists of two parts, one is nonsubsampled tight frame transform, the other is critically sampled wavelet transform (WT). Embedding watermark into the low-frequency sub-band of SSWT, the imperceptibility and robustness of watermark can be significantly improved comparing with some existing watermarking schemes. Experimental results show that proposed blind watermarking scheme is robust against JPEG compression, Gaussian noise, Wiener filtering and median filtering attacks. For rotation attack, we propose a novel watermarking resynchronization approach, the ideal watermark can be always successfully extracted after resynchronization operation to any angle rotated watermarked image. Experimental results show that the proposed resynchronization approach is considerably effective and feasible.

Improved Texture Retrieval Based on Nonsubsampled Contourlet

This paper presents an improved algorithm of image texture retrieval based on nonsubsampled contourlet transform and grey co-occurrence matrix of image.The new improved algorithm not only depends on coefficients of sub bands by nonsubsampled contourlet transform,but also depends on angular second moment,moment inertia,inverse difference moment,correlation of grey co-occurrence matrix of image.Experimental results demonstrate that the proposed algorithm performs much better than the previous methods.It achieves higher recall precision.