A novel filter for block-based motion estimation

Noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors using block based motion estimation techniques. Similar noises are further introduced when the technique of global motion compensation is applied to obtain 'true' object motion from video sequences, where both the camera and object motions are present. We observe that the performance of the mean and the median filters in removing false motion vectors, for estimating 'true' object motion, is not satisfactory, especially when the size of the object is significantly smaller than the scene. In this paper we introduce a novel filter, named as the Mean-Accumulated-Thresholded (MAT) filter, in order to capture 'true' object motion vectors from video sequences with or without the camera motion (zoom and/or pan). Experimental results on representative standard video sequences are included to establish the superiority of our filter compared with the traditional median and mean filters

Comparison of three commercially available buffy coat pooling sets for the preparation of platelet concentrates

Background: A disposable set for platelet concentrate (PC) preparation by the buffy coat method allows pooling of buffy coats, centrifugation and cell separation with in-line leucocyte filtration. This study compares three commercially available pooling sets in combination with INTERCEPT pathogen inactivation (PI). Materials and methods: Sets for pooling of buffy coats were from Fresenius Kabi (FRE), Macopharma (MAC) and Terumo BCT (TER). Platelet yield, recovery and concentration were compared before and after PI (n = 20). Platelet quality was assessed by annexin V binding, P-selectin expression and PAC1 binding. Results: The TER pooling set had the highest platelet yield (539 044 x 10(11)) compared with MAC (453 +/- 077) and FRE (456 +/- 051) prior to PI. This was the result of a significantly higher platelet concentration in the TER storage bag (141 +/- 012 x 10(6)/L) compared with MAC (118 +/- 019) and FRE (128 +/- 015). However, the TER platelet content decreased by 156% after PI, yielding 455 +/- 047 x 10(11) platelets compared with smaller reductions at 95% for MAC (410 +/- 069) and 44% for FRE (436 +/- 052). None of the individual PC contained >10(6) leucocytes. The pH in TER PC was lower compared with MAC and FRE caused by a higher lactic acid production rate. Consequently, PAC1 binding after TRAP activation was lowest for TER PC on day 6. P-selectin and annexin V were not different between suppliers. Conclusion: This study demonstrates the added value of evaluating the entire component production process when introducing a new consumable. This study helped to inform a decision on what pooling set is ideally suited for routine implementation taking into account PI

Comparison of Algorithms for Baseline Correction of LIBS Spectra for Quantifying Total Carbon in Brazilian Soils

LIBS is a promising and versatile technique for multi-element analysis that usually takes less than a minute and requires minimal sample preparation and no reagents. Despite the recent advances in elemental quantification, the LIBS still faces issues regarding the baseline produced by background radiation, which adds non-linear interference to the emission lines. In order to create a calibration model to quantify elements using LIBS spectra, the baseline has to be properly corrected. In this paper, we compared the performance of three filters to remove random noise and five methods to correct the baseline of LIBS spectra for the quantification of total carbon in soil samples. All combinations of filters and methods were tested, and their parameters were optimized to result in the best correlation between the corrected spectra and the carbon content in a training sample set. Then all combinations with the optimized parameters were compared with a separate test sample set. A combination of Savitzky-Golay filter and 4S Peak Filling method resulted in the best correction: Pearson's correlation coefficient of 0.93 with root mean square error of 0.21. The result was better than using a linear regression model with the carbon emission line 193.04 nm (correlation of 0.91 with error of 0.26). The procedure proposed here opens a new possibility to correct the baseline of LIBS spectra and to create multivariate methods based on the a given spectral range.Comment: 13 pages, 5 figure

A new Edge Detector Based on Parametric Surface Model: Regression Surface Descriptor

In this paper we present a new methodology for edge detection in digital images. The first originality of the proposed method is to consider image content as a parametric surface. Then, an original parametric local model of this surface representing image content is proposed. The few parameters involved in the proposed model are shown to be very sensitive to discontinuities in surface which correspond to edges in image content. This naturally leads to the design of an efficient edge detector. Moreover, a thorough analysis of the proposed model also allows us to explain how these parameters can be used to obtain edge descriptors such as orientations and curvatures. In practice, the proposed methodology offers two main advantages. First, it has high customization possibilities in order to be adjusted to a wide range of different problems, from coarse to fine scale edge detection. Second, it is very robust to blurring process and additive noise. Numerical results are presented to emphasis these properties and to confirm efficiency of the proposed method through a comparative study with other edge detectors.Comment: 21 pages, 13 figures and 2 table

Distance Measures for Reduced Ordering Based Vector Filters

Reduced ordering based vector filters have proved successful in removing long-tailed noise from color images while preserving edges and fine image details. These filters commonly utilize variants of the Minkowski distance to order the color vectors with the aim of distinguishing between noisy and noise-free vectors. In this paper, we review various alternative distance measures and evaluate their performance on a large and diverse set of images using several effectiveness and efficiency criteria. The results demonstrate that there are in fact strong alternatives to the popular Minkowski metrics

ElfStore: A Resilient Data Storage Service for Federated Edge and Fog Resources

Edge and fog computing have grown popular as IoT deployments become wide-spread. While application composition and scheduling on such resources are being explored, there exists a gap in a distributed data storage service on the edge and fog layer, instead depending solely on the cloud for data persistence. Such a service should reliably store and manage data on fog and edge devices, even in the presence of failures, and offer transparent discovery and access to data for use by edge computing applications. Here, we present Elfstore, a first-of-its-kind edge-local federated store for streams of data blocks. It uses reliable fog devices as a super-peer overlay to monitor the edge resources, offers federated metadata indexing using Bloom filters, locates data within 2-hops, and maintains approximate global statistics about the reliability and storage capacity of edges. Edges host the actual data blocks, and we use a unique differential replication scheme to select edges on which to replicate blocks, to guarantee a minimum reliability and to balance storage utilization. Our experiments on two IoT virtual deployments with 20 and 272 devices show that ElfStore has low overheads, is bound only by the network bandwidth, has scalable performance, and offers tunable resilience.Comment: 24 pages, 14 figures, To appear in IEEE International Conference on Web Services (ICWS), Milan, Italy, 201