Droplet Image Feedback Control System in Evaporation Experiment

In order to realize the steady-state droplet evaporation, image feedback control system is designed based on DSP. The system has three main functions: to capture and store droplet images during the experiment; to calculate droplet geometrical and physical parameters such as volume, surface area, surface tension and evaporation velocity at a high-precision level; to keep the droplet volume constant. The DSP can drive an injection controller with the PID control to inject liquid so as to keep the droplet volume constant. The evaporation velocity of droplet can be calculated by measuring the injected volume during the evaporation. The structure of hardware and software of the control system, key processing methods such as contour fitting and experimental results are described.

Detection of avian influenza virus subtype H5 using a biosensor based on imaging ellipsometry

A novel method is reported for the detection of avian influenza virus subtype H5 using a biosensor based on high spatial resolution imaging ellipsometry (IE). Monoclonal antibodies specific to H5 hemagglutinin protein were immobilized on silicon wafers and used to capture virus particles. Resultant changes on the surface of the wafers were visualized directly in gray-scale on an imaging ellipsometry image. This preliminary study has shown that the assay is rapid and specific for the identification of avian influenza virus subtype H5. Compared with lateral-flow immunoassays, this biosensor not only has better sensitivity, but can also simultaneously perform multiplexed tests. These results suggest that this biosensor might be a valuable diagnostic toot for avian influenza virus detection. (c) 2009 Elsevier B.V. All rights reserved.

Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

An integrated aurora image retrieval system: AuroraEye

With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset. (c) 2010 Elsevier Inc. All rights reserved.

A Unified Tensor Level Set for Image Segmentation

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt-and pepper-type noise. Second, considering the local geometrical features, e. g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

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.