Geometric Distortion Insensitive Image Watermarking in Affine Covariant Regions

Feature-based image watermarking schemes, which aim to survive various geometric distortions, have attracted great attention in recent years. Existing schemes have shown robustness against rotation, scaling, and translation, but few are resistant to cropping, nonisotropic scaling, random bending attacks (RBAs), and affine transformations. Seo and Yoo present a geometrically invariant image watermarking based on affine covariant regions (ACRs) that provide a certain degree of robustness. To further enhance the robustness, we propose a new image watermarking scheme on the basis of Seo's work, which is insensitive to geometric distortions as well as common image processing operations. Our scheme is mainly composed of three components: 1) feature selection procedure based on graph theoretical clustering algorithm is applied to obtain a set of stable and nonoverlapped ACRs; 2) for each chosen ACR, local normalization, and orientation alignment are performed to generate a geometrically invariant region, which can obviously improve the robustness of the proposed watermarking scheme; and 3) in order to prevent the degradation in image quality caused by the normalization and inverse normalization, indirect inverse normalization is adopted to achieve a good compromise between the imperceptibility and robustness. Experiments are carried out on an image set of 100 images collected from Internet, and the preliminary results demonstrate that the developed method improves the performance over some representative image watermarking approaches in terms of robustness.

Image Ratio Features for Facial Expression Recognition Application

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e. g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

A Relay Level Set Method for Automatic Image Segmentation

This paper presents a new image segmentation method that applies an edge-based level set method in a relay fashion. The proposed method segments an image in a series of nested subregions that are automatically created by shrinking the stabilized curves in their previous subregions. The final result is obtained by combining all boundaries detected in these subregions. The proposed method has the following three advantages: 1) It can be automatically executed without human-computer interactions; 2) it applies the edge-based level set method with relay fashion to detect all boundaries; and 3) it automatically obtains a full segmentation without specifying the number of relays in advance. The comparison experiments illustrate that the proposed method performs better than the representative level set methods, and it can obtain similar or better results compared with other popular segmentation algorithms.

Buildup of gold nanoparticle multilayer thin films based on the covalent-bonding interaction between boronic acids and polyols

A novel method for the fabrication of gold nanoparticle multilayer films based on the covalent-bonding interaction between boronic acid and polyols, poly(vinyl alcohol) (PVA), was developed. The multilayer buildup was monitored by UV-vis absorbance, spectroscopy, which showed a linear increase of the film absorbance with the number of adsorbed Au layers and indicated the stepwise and uniform assembling process. The atomic force microscopy (AFM) image showed that a compact gold multilayer thin film was successfully assembled. The residual boronic acid group on the surface of thin film Could incorporate glycosylated-protein horseradish peroxidase (HRP), and good catalytic activity for H2O2 could be observed.

Wind-vector estimation for RADARSAT-1 SAR images: Validation of wind-direction estimates based upon geometry diversity

In this letter, a new wind-vector algorithm is presented that uses radar backscatter sigma(0) measurements at two adjacent subscenes of RADARSAT-1 synthetic aperture radar (SAR) images, with each subscene having slightly different geometry. Resultant wind vectors are validated using in situ buoy measurements and compared with wind vectors determined from a hybrid wind-retrieval model using wind directions determined by spectral analysis of wind-induced image streaks and observed by colocated QuikSCAT measurements. The hybrid wind-retrieval model consists of CMOD-IFR2 [applicable to C-band vertical-vertical (W) polarization] and a C-band copolarization ratio according to Kirchhoff scattering. The new algorithm displays improved skill in wind-vector estimation for RADARSAT-1 SAR data when compared to conventional wind-retrieval methodology. In addition, unlike conventional methods, the present method is applicable to RADARSAT-1 images both with and without visible streaks. However, this method requires ancillary data such as buoy measurements to resolve the ambiguity in retrieved wind direction.

Flow cytometry and ultrastructure of cryopreserved red seabream (Pagrus major) sperm

The objectives were to assess motility, fertilizing capacity, structural integrity, and mitochondrial function in fresh versus frozen-thawed (15% DMSO was used as a cryoprotectant) sperm from red seabrearn (Pagrus major). Mean (+/- S.D.) rates of motility, fertilization and hatching of frozen-thawed sperm were 81.0 +/- 5.4, 92.8 +/- 1.9, and 91.8 +/- 5.2%, respectively; for fresh sperm, they were 87.5 +/- 7.7, 95.8 +/- 2.4, and 93.8 +/- 4.2%. Although motility was lower in frozen-thawed versus fresh sperm (P < 0.05), there was no effect (P > 0.05) of cryopreservation on fertilization or hatching. Based on scanning and transmission electron microscopy, 77.8 +/- 5.6% of fresh sperm had normal morphology, whereas for frozen-thawed sperm, 63.0 +/- 7.2% had normal morphology, 20.6 +/- 3.1% were slightly damaged (e.g. swelling or rupture of head, mid-piece and tail region as well as mitochondria), and 16.4 +/- 4.2% were severely damaged. Sperm were stained with propidium iodide and Rhodamine 123 to assess plasma membrane integrity and mitochondrial function, respectively, and examined with flow cytometry. For fresh sperm, 83.9% had an intact membrane and functional mitochondria, whereas for frozen-thawed sperm, 74.8% had an intact membrane and functional mitochondria, 12.7% had a damaged membrane, 9.9% had nonfunctional mitochondria, and 2.6% had both a damaged membrane and nonfunctional mitochondria. In conclusion, ultrastructure and flow cytometry were valuable for assessment of frozen-thawed sperm quality; cryopreservation damaged the sperm but fertilizing ability was not significantly decreased. (c) 2007 Elsevier Inc. All rights reserved.

An Efficient Correspondence Based Algorithm for 2D and 3D Model Based Recognition

A polynomial time algorithm (pruned correspondence search, PCS) with good average case performance for solving a wide class of geometric maximal matching problems, including the problem of recognizing 3D objects from a single 2D image, is presented. Efficient verification algorithms, based on a linear representation of location constraints, are given for the case of affine transformations among vector spaces and for the case of rigid 2D and 3D transformations with scale. Some preliminary experiments suggest that PCS is a practical algorithm. Its similarity to existing correspondence based algorithms means that a number of existing techniques for speedup can be incorporated into PCS to improve its performance.

Context-Based Vision System for Place and Object Recognition

While navigating in an environment, a vision system has to be able to recognize where it is and what the main objects in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is to identify familiar locations (e.g., office 610, conference room 941, Main Street), to categorize new environments (office, corridor, street) and to use that information to provide contextual priors for object recognition (e.g., table, chair, car, computer). We present a low-dimensional global image representation that provides relevant information for place recognition and categorization, and how such contextual information introduces strong priors that simplify object recognition. We have trained the system to recognize over 60 locations (indoors and outdoors) and to suggest the presence and locations of more than 20 different object types. The algorithm has been integrated into a mobile system that provides real-time feedback to the user.

Robust 2-D Model-Based Object Recognition

Techniques, suitable for parallel implementation, for robust 2D model-based object recognition in the presence of sensor error are studied. Models and scene data are represented as local geometric features and robust hypothesis of feature matchings and transformations is considered. Bounds on the error in the image feature geometry are assumed constraining possible matchings and transformations. Transformation sampling is introduced as a simple, robust, polynomial-time, and highly parallel method of searching the space of transformations to hypothesize feature matchings. Key to the approach is that error in image feature measurement is explicitly accounted for. A Connection Machine implementation and experiments on real images are presented.

Three-Dimensional Recognition of Solid Objects from a Two-Dimensional Image

This thesis addresses the problem of recognizing solid objects in the three-dimensional world, using two-dimensional shape information extracted from a single image. Objects can be partly occluded and can occur in cluttered scenes. A model based approach is taken, where stored models are matched to an image. The matching problem is separated into two stages, which employ different representations of objects. The first stage uses the smallest possible number of local features to find transformations from a model to an image. This minimizes the amount of search required in recognition. The second stage uses the entire edge contour of an object to verify each transformation. This reduces the chance of finding false matches.

Image Chunking: Defining Spatial Building Blocks for Scene Analysis

Rapid judgments about the properties and spatial relations of objects are the crux of visually guided interaction with the world. Vision begins, however, with essentially pointwise representations of the scene, such as arrays of pixels or small edge fragments. For adequate time-performance in recognition, manipulation, navigation, and reasoning, the processes that extract meaningful entities from the pointwise representations must exploit parallelism. This report develops a framework for the fast extraction of scene entities, based on a simple, local model of parallel computation.sAn image chunk is a subset of an image that can act as a unit in the course of spatial analysis. A parallel preprocessing stage constructs a variety of simple chunks uniformly over the visual array. On the basis of these chunks, subsequent serial processes locate relevant scene components and assemble detailed descriptions of them rapidly. This thesis defines image chunks that facilitate the most potentially time-consuming operations of spatial analysis---boundary tracing, area coloring, and the selection of locations at which to apply detailed analysis. Fast parallel processes for computing these chunks from images, and chunk-based formulations of indexing, tracing, and coloring, are presented. These processes have been simulated and evaluated on the lisp machine and the connection machine.

Festival Images: brand image and stakeholders' brand relationship types at the Edinburgh Festival Fringe.

The Edinburgh Festival Fringe (The Fringe) is the largest arts festival in the world and it has inspired the creation of similar festivals world-wide. Since its conception in 1947, the Fringe has demonstrated significant growth in visitor numbers; ticket sales; and its economic contribution. Despite this, the sustainable future of Edinburgh’s festivals is debated as Edinburgh, ‘the Festival City’, faces threats from other festival destinations. Festivals position Edinburgh creatively in contrast to the city’s traditionally perceived image as a cultural-historic centre. Despite this, little research has been undertaken into the creative and cultural significance of Edinburgh’s festivals, including the Fringe. This interdisciplinary research grounded in marketing, tourism, and festival and event management; and underpinned by constructivism, presents an understanding of types of brand relationships that exist between the Fringe and its primary stakeholders. This is achieved through defining both the Fringe brand image and its primary stakeholders; and applying these definitions to the development of a typology of Fringe-stakeholders’ brand relationships. The significance of this study is evident within its topic of inquiry and the research methods applied. In the little-considered arena of arts festivals and their stakeholders, this is the first in-depth study into the Fringe as a festival and festival brand. Within this, the definition of a Fringe brand image contributes to understanding the cultural and creative significance of the Fringe. Furthermore, this research contributes a unique understanding of the types of stakeholders that are engaged with the Fringe. The types of brand relationships that exist between these stakeholders and the Fringe are another significant contribution to knowledge and understanding. While specific to the present context, these findings may prove transferable to further festivals or events, and related areas and industries. The contribution made by this research to the methodological developments in festival and event studies is of additional significance. The application of visual research methods, including semiotic analysis and photo-elicitation within phenomenological interviews, has previously been applied in marketing, consumer, and tourism research, but not to the understanding of festival brands and stakeholders’ brand relationship types. Findings of this research illustrate that existing marketing and consumer brand frameworks and stakeholder theories are applicable to festivals. Further, it is possible to define ‘a’ Fringe brand image which is subjective and contradictory. The unique open-access and organic, operational model of the Fringe facilitates its many contributors, and consumers. Fringe stakeholders may be categorised according to their level of engagement with the Fringe (as primary or secondary) and their particular stakeholder role(s), which are varied and multiple. Fringe-stakeholder brand relationship types are overwhelmingly positive; and are based upon interpersonal relationship dimensions (including friendships, marriages, kinships and partnerships). Fringe-stakeholder brand relationship types can be classified therefore as having similar dimensions to those brand relationship types previously described for consumer products and brands.

Learning and Reuse of Experience in Behavior-Based Service Robots

M.H.Lee, Q. Meng and H. Holstein, ?Learning and Reuse of Experience in Behavior-Based Service Robots?, Seventh International Conference on Control, Automation, Robotics and Vision (ICARCV2002), pp1019-24, December 2002, Singapore

Accurate Range Image Registration: Eliminating or Modelling Outliers

Liu, Yonghuai, Liu, Honghai, Li, Longzhuang, Wei, Baogang. Accurate Range Image Registration: Eliminating or Modelling Outliers. Proceedings of 12th IEEE Conference on Emerging Technologies and Factory Automation, 2007, pp. 1316-1323. Sponsorship: IEEE

Using hybrid knowledge engineering and image processing in color virtual restoration of ancient murals

IEEE Transactions on Knowledge and Data Engineering, vol. 15, no. 5, pp. 1338-1343, 2003.