7804224
Level-set based geometric colour snake with region support
A novel method is introduced to force a geometric-based snake be more tolerant towards weak edges and noise in images. The method integrates gradient flow forces with region constraints obtained from diffused region segmentation forces. The diffusion is obtained from the region map vector flow field. This extra region force gives the snake a global view of the boundary information within the image. We present results on both graylevel and colour images.
1308804
Texture Exemplars for Defect Detection on Random Textures
We present a new approach to detecting defects in random textures which requires only very few defect free samples for unsupervised training. Each product image is divided into overlapping patches of various sizes. Then, density mixture models are applied to reduce groupings of patches to a number of textural exemplars, referred to here as texems, characterising the means and covariances of whole sets of image patches. The texems can be viewed as implicit representations of textural primitives. A multiscale approach is used to save computational costs. Finally, we perform novelty detection by applying the lower bound of normal samples likelihoods on the multiscale defect map of an image to localise defects.
12048322
Inspecting Colour Tonality on Textured Surfaces
We present a multidimensional histogram method to inspect tonality on colour textured surfaces, e.g. ceramic tiles. Comparison in the noise dominated chromatic channels is error prone. We perform vector- ordered colour smoothing and generate a PCA-based reconstruction of a query tile based on a reference tile eigenspace. Histograms of local feature vectors are then compared for tonality defect detection. The proposed method is compared and evaluated on a data set with groundtruth.
22043660
Colour tonality inspection using eigenspace features
In industrial quality inspection of colour texture surfaces, such as ceramic tiles or fabrics, it is important to maintain a consistent colour shade or tonality during production. We present a multidimensional histogram method using a novelty detection scheme to inspect the surfaces. The image noise, introduced by the imaging system, is found mainly to affect the chromatic channels. For colour tonality inspection, the difference between images is very subtle and comparison in the noise dominated chromatic channels is error prone. We perform vector-ordered colour smoothing and extract a localised feature vector at each pixel. The resulting histogram represents an encapsulation of local and global information. Principal component analysis (PCA) is performed on this multidimensional feature space of an automatically selected reference image to obtain reliable colour shade features, which results in a reference eigenspace. Then unseen product images are projected onto this eigenspace and compared for tonality defect detection using histogram comparison. The proposed method is compared and evaluated on a data set with groundtruth.
6641983
An adaptive web page layout structure for small devices
The limited display size of current small Internet devices is becoming a serious obstacle to information access. In this paper, we introduce a Document REpresentation for Scalable Structures (DRESS) to help information providers make composite documents, typically web pages, scalable in both logic and layout structure to support effective information acquisition in heterogeneous environments. Through this novel document representation structure based on binary slicing trees, the document can dynamically adapt its presentation according to display sizes by maximizing the information throughput to users. We discuss the details of this structure with its key attributes. An automatic approach for generating this structure for existing web pages is also presented. A branch-and-bound algorithm and a capacity ratio-based slicing method are proposed to select proper content representation and aesthetic document layouts respectively. A set of user study experiments have been carried out and the results show that compared with the thumbnail-based approach, the DRESS-based interface can reduce browsing time by 23.5%.
1573020
Automatic browsing of large pictures on mobile devices
Pictures have become increasingly common and popular in mobile communications. However, due to the limitation of mobile devices, there is a need to develop new technologies to facilitate the browsing of large pictures on the small screen. In this paper, we propose a novel approach which is able to automate the scrolling and navigation of a large picture with a minimal amount of user interaction on mobile devices. An image attention model is employed to illustrate the information structure within an image. An optimal image browsing path is then calculated based on the image attention model to simulate the human browsing behaviors. Experimental evaluations of the proposed mechanism indicate that our approach is an effective way for viewing large images on small displays.
5342027
Attention model based progressive image transmission
Progressive image transmission provides a convenient user interface when images are transmitted slowly. However, most of the existing PIT techniques only consider the objective quality of the reconstructed image. Here we present an attention model based progressive image transmission approach to improve the subjective quality of the transmission process. We use both bottom-up image features and top-down semantic information to extract the regions of interest and also propose a new ROI coding scheme based on JPEG2000 to control the trade-off between the transmission of ROI and background. Experiments have shown the efficiency of our approach
307226
Selectively Grouping Neurons in Recurrent Networks of Lateral Inhibition
Winner-take-all networks have been proposed to underlie many of the brain's fundamental computational abilities. However, notmuchisknown about how to extend the grouping of potential winners in these networks beyond single neuron or uniformly arranged groups of neurons. We show that competition between arbitrary groups of neurons can be realized by organizing lateral inhibition in linear threshold networks. Given a collection of potentially overlapping groups (with the exception of some degenerate cases), the lateral inhibition results in network dynamics such that any permitted set of neurons that can be coactivated by some input at a stable steady state is contained in one of the groups. The information about the input is preserved in this operation. The activity level of a neuron in a permitted set corresponds to its stimulus strength, amplified by some constant. Sets of neurons that are not part of a group cannot be coactivated by any input at a stable steady state. We analyze the storage capacity of such a network for random groupsthe number of random groups the network can store as permitted sets without creating too many spurious ones. In this framework, we calculate the optimal sparsity of the groups (maximizing group entropy). We find that for dense inputs, the optimal sparsity is unphysiologically small. However, when the inputs and the groups are equally sparse, we derive a more plausible optimal sparsity. We believe our results are the first steps toward attractor theories in hybrid analog-digital networks.
39255438
Design of progressive auctions for procurement based on Lagrangian relaxation
Auction mechanisms have been found successful in implementing e-procurement, with the buyer as the auctioneer and the sellers as the bidders. Single round auctions are prevalently used in e-procurement, in which the suppliers submit sealed bids in response to the buyer's request-for-quote. The bid evaluation problem faced by the buyer is an optimization problem that selects the winning bids to minimize the cost of procurement. Though these auction types are advantageous in many scenarios, progressive auctions (multiple rounds) are preferred in terms of information elicitation and bid preparation. This paper demonstrates the design of progressive auctions, from their single-round counterparts, using Lagrangian relaxation. In particular, we show that an appropriate algorithm for a judiciously selected Lagrangian relaxation of the bid evaluation problem, can help in designing a progressive auction. The procurement of multiple units of a single item is considered with linear and piecewise linear supply curves.