15590248
A Class of Discrete Multiresolution Random Fields and Its Application to Image Segmentation
In this paper, a class of Random Field model, defined on a multiresolution array is used in the segmentation of gray level and textured images. The novel feature of one form of the model is that it is able to segment images containing unknown numbers of regions, where there may be significant variation of properties within each region. The estimation algorithms used are stochastic, but because of the multiresolution representation, are fast computationally, requiring only a few iterations per pixel to converge to accurate results, with error rates of 1-2 percent across a range of image structures and textures. The addition of a simple boundary process gives accurate results even at low resolutions, and consequently at very low computational cost.
32219854
Unsupervised texture segmentation using multiresolution hybrid genetic algorithm
This work approaches the texture segmentation problem by incorporating genetic algorithm and k-mean clustering method within a multiresolution structure. First, a quad-tree structure is constructed and the input image is partition into blocks at different resolution levels. Texture features are then extracted from each block. Based on the texture features, a hybrid genetic algorithm is employed to perform the segmentation. The crossover operator of traditional genetic algorithm is replaced with k-means clustering method while the mutate and select operators are adopted. In the final step, the boundaries and the segmentation result of the current resolution level are propagated down to the next level to act as contextual constraints and the initial configuration of the next level, respectively.
24590909
Fragile watermarking scheme exploiting non-deterministic block-wise dependency
Block-wise dependency is recognized as a key requirement in fragile watermarking schemes to thwart the vector quantization (VQ) attack. It has also been observed that deterministic dependency is still susceptible to transplantation attack or even simple cover-up attack. In this work, a new fragile watermarking scheme exploiting non-deterministic dependency is proposed. To watermark the original image, each pixel is adjusted according to the consistency between a key-dependent binary watermark bit, the information from the pixel itself and the non-deterministic secret dependency information calculated from a neighborhood centered at that pixel. Localization resolution is enhanced with a post-processing operation on the output difference map.
23059132
Image authentication and integrity verification via content-based watermarks and a public key cryptosystem
A technique using the inherent feature map of the underlying image as the watermark is proposed in this work. First, the binary feature map is extracted as watermark and partitioned into blocks. Secondly, neighboring feature map blocks are blended and encrypted for insertion. On the receiver side, the feature map from the received image is extracted again and compared against the recovered watermark to verify the integrity and authenticity. In addition the capability of detecting geometric transformation, removal of original objects and addition of foreign objects, the proposed scheme is also capable of localizing tampering and detecting cropping without a priori knowledge about the image.
43675712
Unsupervised Image Segmentation using Gibbs Sampler within a Multiresolution Framework
14325657
An approach to reducing the labeling cost of Markov random fields within an infinite label space
This work proposes a novel idea, called SOIL, for reducing the computational complexity of the maximum a posteriori optimization problem using Markov random fields (MRFs). The local characteristics of MRFs are employed so that the searching in a virtually infinite label space is confined in a small finite space. Globally, the number of labels allowed is as many as the number of image sites while locally the optimal label is sampled from a space consisting of the labels assigned to the four-neighbor plus a random one. Neither the prior knowledge about the number of classes nor the estimation phase of the class number is required in this work. The proposed method is applied to the problem of texture segmentation and the result is compared with those obtained from conventional methods.
29028846
Reuse or Never Reuse the Deleted Labels in XML Query Processing Based on Labeling Schemes
To facilitate the XML query processing, several kinds of labeling schemes have been proposed. Based on the labeling schemes, the ancestor-descendant and parent-child relationships in XML queries can be quickly determined without accessing the original XML file. Recently, more researches are focused on how to update the labels when nodes are inserted into the XML. However how to process the deleted labels are not discussed previously. We think that the deleted labels can be processed in two different directions: (1) reuse all the deleted labels to control the label size increasing speed and improve the query performance; (2) never reuse the deleted labels to query different versions of the XML data based on labeling schemes. In this paper, we firstly introduce our previous work, called QED, which can completely avoid the re-labeling in XML updates. Secondly based on QED we propose a new algorithm, called Reuse, which can reuse all the deleted labels to control the label size increasing speed; meanwhile the Reuse algorithm can completely avoid the re-labeling also. Thirdly to query different versions of the XML data, we propose another new algorithm, called NeverReuse, which is the only approach that never reuses any deleted labels. Extensive experimental results show that the algorithms proposed in this paper can control the label size increasing speed when reusing all the deleted labels, and is the only approach to query different versions of the XML data based on labeling schemes.
8674625
Image coding with modulated wavelets
In this paper, a subband image-coding scheme with adapted modulated wavelets is presented. Due to the fact that Gabor functions mimic well the simple cells of mammalian visual receptive field with optimum localization in the joint space-spatial frequency domain, we divide the image into subbands using discrete Gabor transform; decompose each subband into modulated wavelet (MW) coefficients with adapted modulating frequencies on a subband basis; and encode the complex-valued MW coefficients using the modified SPIHT in an embedded manner. Experimental results show that the proposed MW transform based subband coding is preferable to the wavelet transform based coding for images composed of textures with rapid variation in grays.
39573011
The adaptive modulated wavelet transform image representation
In this paper, a new, called the adaptive modulated wavelet transform (AMWT) image representation is presented. One of the attractive features is that the informative instantaneous frequencies of images can be taken into account to improve the representation performance via adaptation of the modulating frequencies involved. The transform coefficients in both wavelet and modulated wavelet domains are uniformly quantized with several quantization levels. The computed peak signal-to-noise ratio values and entropies are used as rate distortion curves for performance comparison. Experimental results show that AMWT out performs wavelet transform for representing images containing textures with rapid variation in grays.
27555290
Constructing Homogeneous Factorisations of Complete Graphs and Digraphs
Abstract. A homogeneous factorisation of a complete graph Kn is a partition of the edge set that is invariant under a subgroup G of Sn such that G is transitive on the parts of the partition and induces a vertex-transitive automorphism group on the graph corresponding to each part. A product construction is given for such factorisations.
8850461
Schema-guided wrapper maintenance for web-data extraction
Extracting data from Web pages using wrappers is a fundamental problem arising in a large variety of applications of vast practical interests. There are two main issues relevant to Web-data extraction, namely wrapper generation and wrapper maintenance. In this paper, we propose a novel schema-guided approach to the problem of automatic wrapper maintenance. It is based on the observation that despite various page changes, many important features of the pages are preserved, such as syntactic patterns, annotations, and hyperlinks of the extracted data items. Our approach uses these preserved features to identify the locations of the desired values in the changed pages, and repair wrappers correspondingly by inducing semantic blocks from the HTML tree. Our intensive experiments on real Web sites show that the proposed approach can effectively maintain wrappers to extract desired data with high accuracies.