64 resultados para foreground object removal


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In this paper we present a segmentation algorithm to extract foreground object motion in a moving camera scenario without any preprocessing step such as tracking selected features, video alignment, or foreground segmentation. By viewing it as a curve fitting problem on advected particle trajectories, we use RANSAC to find the polynomial that best fits the camera motion and identify all trajectories that correspond to the camera motion. The remaining trajectories are those due to the foreground motion. By using the superposition principle, we subtract the motion due to camera from foreground trajectories and obtain the true object-induced trajectories. We show that our method performs on par with state-of-the-art technique, with an execution time speed-up of 10x-40x. We compare the results on real-world datasets such as UCF-ARG, UCF Sports and Liris-HARL. We further show that it can be used toper-form video alignment.

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Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.

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Salient object detection has become an important task in many image processing applications. The existing approaches exploit background prior and contrast prior to attain state of the art results. In this paper, instead of using background cues, we estimate the foreground regions in an image using objectness proposals and utilize it to obtain smooth and accurate saliency maps. We propose a novel saliency measure called `foreground connectivity' which determines how tightly a pixel or a region is connected to the estimated foreground. We use the values assigned by this measure as foreground weights and integrate these in an optimization framework to obtain the final saliency maps. We extensively evaluate the proposed approach on two benchmark databases and demonstrate that the results obtained are better than the existing state of the art approaches.

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A method has been developed for the removal of chromium using ferrous sulphide generated in situ. The effects of experimental parameters such as pH, reagent dosages, interference from cations and chelating agents have been investigated. Under optimum conditions, removal efficiencies of 99 and 97% for synthetic and industrial samples have been obtained. The method offers all the advantages of sulphide precipitation process and can be adopted easily for industrial effluents.

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An iterative algorithm baaed on probabilistic estimation is described for obtaining the minimum-norm solution of a very large, consistent, linear system of equations AX = g where A is an (m times n) matrix with non-negative elements, x and g are respectively (n times 1) and (m times 1) vectors with positive components.

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We present a motion detection algorithm which detects direction of motion at sufficient number of points and thus segregates the edge image into clusters of coherently moving points. Unlike most algorithms for motion analysis, we do not estimate magnitude of velocity vectors or obtain dense motion maps. The motivation is that motion direction information at a number of points seems to be sufficient to evoke perception of motion and hence should be useful in many image processing tasks requiring motion analysis. The algorithm essentially updates the motion at previous time using the current image frame as input in a dynamic fashion. One of the novel features of the algorithm is the use of some feedback mechanism for evidence segregation. This kind of motion analysis can identify regions in the image that are moving together coherently, and such information could be sufficient for many applications that utilize motion such as segmentation, compression, and tracking. We present an algorithm for tracking objects using our motion information to demonstrate the potential of this motion detection algorithm.

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Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

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Alum-impregnated activated alumina (AIAA) was investigated in the present work as an adsorbent for the removal of As(V) from water by batch mode. Adsorption study at different pH values shows that the efficiency of AIAA is much higher than as such activated alumina and is suitable for treatment of drinking water. The adsorption isotherm experiments indicated that the uptake of As(V) increased with increasing As(V) concentration from 1 to 25 mg/l and followed Langmuir-type adsorption isotherm. Speciation diagram shows that in the pH range of 2.8–11.5, arsenate predominantly exists as H2AsO4− and HAsO42− species and hence it is presumed that these are the major species being adsorbed on the surface of AIAA. Intraparticle diffusion and kinetic studies revealed that adsorption of As(V) was due to physical adsorption as well as through intraparticle diffusion. Effect of interfering ions revealed that As(V) sorption is strongly influenced by the presence of phosphate ion. The presence of arsenic on AIAA is depicted from zeta potential measurement, scanning electron microscopy (SEM) and energy-dispersive analysis of X-ray (EDAX) mapping study. Alum-impregnated activated alumina successfully removed As(V) to below 40 ppb (within the permissible limit set by WHO) from water, when the initial concentration of As(V) is 10 mg/l.

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In document images, we often find printed lines over-lapping with hand written elements especially in case of signatures. Typical examples of such images are bank cheques and payment slips. Although the detection and removal of the horizontal lines has been addressed, the restoration of the handwritten area after removal of lines, persists to be a problem of interest. lit this paper, we propose a method for line removal and restoration of the erased areas of the handwritten elements. Subjective evaluation of the results have been conducted to analyze the effectiveness of the proposed method. The results are promising with an accuracy of 86.33%. The entire Process takes less than half a second for completion on a 2.4 GHz 512 MB RAM Pentium IV PC for a document image.

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Raffinose oligosaccharides (RO) are the major factors responsible for flatulence following ingestion of soybean-derived products. Removal of RO from seeds or soymilk would then have a positive impact on the acceptance of soy-based foods. In this study, alpha-galactosidase from Aspergillus oryzae was entrapped in gelatin using formaldehyde as the hardener. The immobilization yield was 64.3% under the optimum conditions of immobilization. The immobilized alpha-galactosidase showed a shift in optimum pH from 4.8 to 5.4 in acetate buffer. The optimum temperature also shifted from 50 degrees C to 57 degrees C compared with soluble enzyme. Immobilized alpha-galactosidase was used in batch, repeated batch and continuous mode to degrade RO present in soymilk. In the repeated batch, 45% reduction of RO was obtained in the fourth cycle. The performance of immobilized alpha-galactosidase was tested in a fluidized bed reactor at different flow rates and 86% reduction of RO in soymilk was obtained at 25 ml h(-1) flow rate. The study revealed that immobilized alpha-galactosidase in continuous mode is efficient in reduction of RO present in soymilk.

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Feature track matrix factorization based methods have been attractive solutions to the Structure-front-motion (Sfnl) problem. Group motion of the feature points is analyzed to get the 3D information. It is well known that the factorization formulations give rise to rank deficient system of equations. Even when enough constraints exist, the extracted models are sparse due the unavailability of pixel level tracks. Pixel level tracking of 3D surfaces is a difficult problem, particularly when the surface has very little texture as in a human face. Only sparsely located feature points can be tracked and tracking error arc inevitable along rotating lose texture surfaces. However, the 3D models of an object class lie in a subspace of the set of all possible 3D models. We propose a novel solution to the Structure-from-motion problem which utilizes the high-resolution 3D obtained from range scanner to compute a basis for this desired subspace. Adding subspace constraints during factorization also facilitates removal of tracking noise which causes distortions outside the subspace. We demonstrate the effectiveness of our formulation by extracting dense 3D structure of a human face and comparing it with a well known Structure-front-motion algorithm due to Brand.

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The commercial acrylic fibre "Cashmilon" was partially hydrolyzed to convert a fraction of its nitrile (-CN) groups to carboxylic acid (-COOH) groups and then coated with polyethylenimine (PEI) resin and cross-linked with glutaraldehyde to produce a novel gel-coated fibrous sorbent with multiple functionalities of cationic, anionic and chelating types, and significantly faster sorption kinetics than bead-form sorbents. The sorption properties of the fibrous sorbent were measured using Zn(II) in aqueous solution as the sorbate to determine the effects of pH and the presence of common ions in the solution on the sorption capacity. The rate of sorption on the gel-coated fibre was measured in comparison with that on Amberlite IRA-68 weak-base resin beads, to demonstrate the marked difference between fibre and bead-form sorbents in their kinetic behaviour.

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The commercial acrylic fibre "Cashmilon" was partially hydrolyzed to convert a fraction of its nitrile (-CN) groups to carboxylic acid (-COOH) groups and then coated with polyethylenimine (PEI) resin and cross-linked with glutaraldehyde to produce a novel gel-coated fibrous sorbent with multiple functionalities of cationic, anionic and chelating types, and significantly faster sorption kinetics than bead-form sorbents. The sorption properties of the fibrous sorbent were measured using Zn(II) in aqueous solution as the sorbate to determine the effects of pH and the presence of common ions in the solution on the sorption capacity. The rate of sorption on the gel-coated fibre was measured in comparison with that on Amberlite IRA-68 weak-base resin beads, to demonstrate the marked difference between fibre and bead-form sorbents in their kinetic behaviour.

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A commercial acrylic fiber with 92% (w/w) acrylonitrile content was partially hydrolyzed converting a fraction of the nitrile (-CN) groups to carboxylic acid (-COOH) groups, to coat the fiber with polyethylenimine (PEI) resin, which was then crosslinked with glutaraldehyde and further quaternized with ethyl chloroacetate to produce a novel strong-base anionic exchanger in the form of fiber. Designated as PAN(QPEI.XG)(Cl-), the fibrous sorbent was compared with a commercial bead-form resin Amberlite IRA-458(Cl-) in respect of sorption capacity, selectivity, and kinetics for removal of silver thiosulfate complexes from aqueous solutions. Though the saturation level of [Ag(S2O3)(2)](3-) on PAN(QPEI.XG)(Cl-) is considerably less than that on IRA-458(Cl-), the gel-coated fibrous sorbent exhibits, as compared to the bead-form sorbent, a significantly higher sorption selectivity for the silver thiosulfate complex in the presence of excess of other anions Such as S2O32-, SO42-, and Cl-, and a remarkably faster rate of both sorption and stripping. The initial uptake of the sorbate by the fibrous sorbent is nearly instantaneous, reaching up to similar to 80% of the saturation capacity within 10 s, as compared to only similar to 12% on the bead-form sorbent. The high initial rate of uptake fits a shell-core kinetic model for sorption on fiber of cylindrical geometry. With 4M HCl, the stripping of the sorbed silver complex from the fibrous sorbent is clean and nearly instantaneous, while, in contrast, a much slower rate of stripping on the bead-form sorbent leads to its fouling due to a slow decomposition of the silver thiosulfate complex in the acidic medium.

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The utility of rice husk as an adsorbent for metal ions such as iron, zinc and copper from acid mine water was assessed. The adsorption isotherms exhibited Langmuirian behavior and were endothermic in nature. The free energy values for adsorption of the chosen metal ions onto rice husk were found to be highly negative attesting to favorable interaction. Over 99% Fe3+, 98% of Fe2+ and Zn2+ and 95% Cu2+ uptake was achieved from acid mine water, with a concomitant increase in the pH value by two units using rice husk. The remediation studies carried out on acid mine water and simulated acid mine water pretreated with rice husk indicated successful growth of Desulfotomaculum nigrificans (D. nigrificans). The amount of sulphate bioreduction in acid mine water at an initial pH of 5.3 was enhanced by D. nigrificans from 21% to 40% in the presence of rice husk filtrate supplemented with carbon and nitrogen. In simulated acid mine water with fortified husk filtrate, the sulphate reduction was even more extensive, with an enhancement to 73%. Concurrently, almost 90% Fe2+, 89% Zn2+ and 75% Cu2+ bioremoval was attained from simulated acid mine water. Metal adsorption by rice husk was confirmed in desorption experiments in which almost complete removal of metal ions from the rice husk was achieved after two elutions using 1 M HCl. The possible mechanisms of metal ion adsorption onto rice husk and sulphate reduction using D. nigrificans are discussed.