CMA:an efficient index algorithmof clustering supporting fast retrieval oflarge image databases

To realize content-hased retrieval of large image databases, it is required to develop an efficient index and retrieval scheme. This paper proposes an index algorithm of clustering called CMA, which supports fast retrieval of large image databases. CMA takes advantages of k-means and self-adaptive algorithms. It is simple and works without any user interactions. There are two main stages in this algorithm. In the first stage, it classifies images in a database into several clusters, and automatically gets the necessary parameters for the next stage-k-means iteration. The CMA algorithm is tested on a large database of more than ten thousand images and compare it with k-means algorithm. Experimental results show that this algorithm is effective in both precision and retrieval time.

Dataset of Large Gathering Images for Person Identification and Tracking

This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises of Masjid Al-Nabvi,Madinah,Saudi Arabia.This dataset consists of raw and processed images reflecting a highly challenging and unconstraint environment.The methodology for building the dataset consists of four core phases;that include acquisition of videos,extraction of frames,localization of face regions,and cropping and resizing of detected face regions.The raw images in the dataset consist of a total of 4613 frames obtained fromvideo sequences.The processed images in the dataset consist of the face regions of 250 persons extracted from raw data images to ensure the authenticity of the presented data.The dataset further consists of 8 images corresponding to each of the 250 subjects(persons)for a total of 2000 images.It portrays a highly unconstrained and challenging environment with human faces of varying sizes and pixel quality(resolution).Since the face regions in video sequences are severely degraded due to various unavoidable factors,it can be used as a benchmark to test and evaluate face detection and recognition algorithms for research purposes.We have also gathered and displayed records of the presence of subjects who appear in presented frames;in a temporal context.This can also be used as a temporal benchmark for tracking,finding persons,activity monitoring,and crowd counting in large crowd scenarios.

Near-Range Large Field-of-View Three-Dimensional Photon-Counting Imaging with a Single-Pixel Si-Avalanche Photodiode

Large field-of-view（FoV） three-dimensional（3 D） photon-counting imaging is demonstrated with a single-pixel single-photon detector based on a Geiger-mode Si-avalanche photodiode. By removing the collecting lens（CL）before the detector, the FoV is expanded to ±10°. Thanks to the high detection efficiency, the signal-to-noise ratio of the imaging system is as high as 7.8 dB even without the CL when the average output laser pulse energy is about 0.45 pJ/pulse for imaging the targets at a distance of 5 m. A 3 D image overlaid with the reflectivity data is obtained according to the photon-counting time-of-flight measurement and the return photon intensity.

Estimation of the turbulent viscous shear stress in a centrifugal rotary blood pump by the large eddy particle image velocimetry method

The non-physiologic turbulent flows in centrifugal rotary blood pumps (RBPs) may result in complications such as the hemolysis and the platelet activation. Recent researches suggest that the turbulent viscous dissipation in the smallest eddies is the main factor of the blood trauma caused by the turbulent flow. The turbulent viscous shear stress (TVSS) was taken as the realistic physical force acting on the cells. However, limited by the temporal and spatial resolutions of the instrumentation currently available, very limited studies are available for the TVSS in the RBPs. In this paper, the large eddy particle image velocimetry (PIV) method is used to estimate the turbulent dissipation rate in the sub-grid scale, to investigate the effect of the TVSS on the blood trauma. Detailed flow characteristics, such as the relative velocity vectors, the estimated TVSS levels and the Kolmogorov length scales, are analyzed in three impeller phases at three constant flow rates (3 L/min, 5 L/min and 7 L/min). Over the measures range in this study, the maximum TVSS in the investigated RBP is lower than the reported critical value of stress. This study demonstrates that the large eddy PIV method is effective to evaluate the flow-dependent force on the cells. On the other hand, it is found that the TVSS is highly dependent on the flow behavior. Under severe off-design conditions, the complex flow characteristics, such as the flow separation and the vortical structures, will increase the TVSS. Thus, in order to reduce the hemolysis in the RBPs, the flow disturbance, induced by the departure of the incidence angle, should be avoided during the design of the RBPs.

A Study of Animated Transition in Similarity-Based Tiled Image Layout

For many information visualization applications, showing the transition when interacting with the data is critically important as it can help users better perceive the changes and understand the underlying data. In this paper, we investigate the effectiveness of animated transition in a tiled image layout where the spiral arrangement of the images is based on their similarity. Three aspects of animated transition are considered, including animation steps, animation actions, and flying paths. Exploring and weighting the advantages and disadvantages of different methods for each aspect and in conjunction with the characteristics of the spiral image layout, we present an integrated solution, called AniMap, for animating the transition from an old layout to a new layout when a different image is selected as the query image. We show the effectiveness of our animated transition solution by demonstrating experimental results and conducting a comparative user study.

Subvoxel light-sheet microscopy for high-resolution high-throughput volumetric imaging of large biomedical specimens

A key challenge when imaging whole biomedical specimens is how to quickly obtain massive cellular information over a large field of view(FOV).We report a subvoxel light-sheet microscopy(SLSM)method enabling high-throughput volumetric imaging of mesoscale specimens at cellular resolution.A nonaxial,continuous scanning strategy is developed to rapidly acquire a stack of large-FOV images with three-dimensional(3-D)nanoscale shifts encoded.Then,by adopting a subvoxel-resolving procedure,the SLSM method models these low-resolution,cross-correlated images in the spatial domain and can iteratively recover a 3-D image with improved resolution throughout the sample.This technique can surpass the optical limit of a conventional light-sheet microscope by more than three times,with high acquisition speeds of gigavoxels per minute.By fast reconstruction of 3-D cultured cells,intact organs,and live embryos,SLSM method presents a convenient way to circumvent the trade-off between mapping large-scale tissue(>100 mm3)and observing single cell(∼1-μm resolution).It also eliminates the need of complicated mechanical stitching or modulated illumination,using a simple light-sheet setup and fast graphics processing unit-based computation to achieve high-throughput,high-resolution 3-D microscopy,which could be tailored for a wide range of biomedical applications in pathology,histology,neuroscience,etc.

3D depth-coded photoacoustic microscopy with a large field of view for human skin imaging

Photoacoustic （PA） microscopy comes with high potential for human skin imaging, since it allows noninvasively high-resolution imaging of the natural hemoglobin at depths of several millimeters. Here, we developed a PA microscopy to achieve high-resolution, high-contrast, and large field of view imaging of skin. A three-dimensional （3D） depth-coding technology was used to encode the depth information in PA images, which is very intuitive for identifying the depth of blood vessels in a two-dimensional image, and the vascular structure can be analyzed at different depths. Imaging results demonstrate that the 3D depth-coded PA microscopy should be translated from the bench to the bedside.

Design and performance of air flow-assisted ionization imaging mass spectrometry system

The imaging mass spectrometry（IMS） technology has experienced a rapid development in recent years.A new IMS technology which is based on air flow assisted ionization（AFAI） was reported.It allows for the convenient pretreatment of the samples and can image a large area of sample in a single measurement with high sensitivity.The AFAI in DESI mode was used as the ion source in this paper.The new IMS method is named AFADESI-IMS.The adoption of assisted air flow makes the sample pretreatment easy and convenient.An optimization of the distance between the ion transport tube and MS orifice increases the sensitivity of the system.For data processing,a program based on MATLAB with the function of numerical analysis was developed.A theoretical imaging resolution of a few hundred microns can be achieved.The composite AFAI-IMS images of different target analytes were imaged with high sensitivity.A typical AFAI-IMS image of the whole-body section of a rat was obtained in a single analytical measurement.The ability to image a large area for relevant samples in a single measurement with high sensitivity and repeatability is a significant advantage.The method has enormous potentials in the MS imaging of large and complicated samples.