An edge-based approach for robust foreground detection

Foreground segmentation is an essential task in many image processing applications and a commonly used approach to obtain foreground objects from the background. Many techniques exist, but due to shadows and changes in illumination the segmentation of foreground objects from the background remains challenging. In this paper, we present a powerful framework for detections of moving objects in real-time video processing applications under various lighting changes. The novel approach is based on a combination of edge detection and recursive smoothing techniques.We use edge dependencies as statistical features of foreground and background regions and define the foreground as regions containing moving edges. The background is described by short- and long-term estimates. Experiments prove the robustness of our method in the presence of lighting changes in sequences compared to other widely used background subtraction techniques

Parallel Processing Of Visual And Motion Saliency From Real Time Video

Extracting moving and salient objects from videos is important for many applications like surveillance and video retargeting .The proposed framework extract foreground objects of interest without any user interaction or the use of any training data(Unsupervised Learning) .To separate foreground and background regions within and across video frames, the proposed method utilizes visual and motion saliency information extracted from the input video. The Smoothing filter is extremely helpful in characterizing fundamental image constituents, i.e. salient edges and can simultaneously reduce insignificant details, thus producing more accurate boundary information. Our proposed model uses smoothing filter to reduce the effect of noise and achieve a better performance. Proposed system uses real time video data input as well as offline data to process using parallel processing technique. A conditional random field can be applied to effectively combine the saliency induced features. To evaluate the performance of saliency detection methods, the precision-recall rate and F-measures are utilized to reliably compare the extracted saliency information. DOI: 10.17762/ijritcc2321-8169.150317

Accurate foreground segmentation without pre-learning

Foreground segmentation has been widely used in many computer vision applications. However, most of the existing methods rely on a pre-learned motion or background model, which will increase the burden of users. In this paper, we present an automatic algorithm without pre-learning for segmenting foreground from background based on the fusion of motion, color and contrast information. Motion information is enhanced by a novel method called support edges diffusion (SED) , which is built upon a key observation that edges of the difference image of two adjacent frames only appear in moving regions in most of the cases. Contrasts in background are attenuated while those in foreground are enhanced using gradient of the previous frame and that of the temporal difference. Experiments on many video sequences demonstrate the effectiveness and accuracy of the proposed algorithm. The segmentation results are comparable to those obtained by other state-of-the-art methods that depend on a pre-learned background or a stereo setup. © 2011 IEEE.published_or_final_versionThe 6th International Conference on Image and Graphics (ICIG 2011), Hefei, Anhui, China, 12-15 August 2011. In Proceedings of the 6th ICIG, 2011, p. 331-33

Chemoattractant-controlled accumulation of coronin at the leading edge of Dictyostelium cells monitored using a green fluorescent protein–coronin fusion protein

AbstractBackground: The highly motile cells of Dictyostelium discoideum rapidly remodel their actin filament system when they change their direction of locomotion either spontaneously or in response to chemoattractant. Coronin is a cytoplasmic actin-associated protein that accumulates at the cortical sites of moving cells and contributes to the dynamics of the actin system. It is a member of the WD-repeat family of proteins and is known to interact with actin–myosin complexes. In coronin null mutants, cell locomotion is slowed down and cytokinesis is impaired.Results We have visualized the redistribution of coronin by fluorescence imaging of motile cells that have been transfected with an expression plasmid containing the coding sequence of coronin fused to the sequence encoding the green fluorescent protein (GFP). This coronin–GFP fusion protein transiently accumulates in the front regions of growth-phase cells, reflecting the changing positions of leading edges and the competition between them. During the aggregation stage, local accumulation of coronin–GFP is biased by chemotactic orientation of the cells in gradients of cAMP. The impairment of cell motility in coronin null mutants shows that coronin has an important function at the front region of the cells. The mutant cells are distinguished by the formation of extended particle-free zones at their front regions, from where pseudopods often break out as blebs. Cytochalasin A reduces the size of these zones, indicating that actin filaments prevent entry of the particles.Conclusion These data demonstrate that coronin is reversibly recruited from the cytoplasm and is incorporated into the actin network of a nascent leading edge, where it participates in the reorganization of the cytoskeleton. Monitoring the dynamics of protein assembly using GFP fusion proteins and fluorescence microscopy promises to be a generally applicable method for studying the dynamics of cytoskeletal proteins in moving and dividing cells

Low complexity video compression using moving edge detection based on DCT coefficients

In this paper, we propose a new low complexity video compression method based on detecting blocks containing moving edges us- ing only DCT coe±cients. The detection, whilst being very e±cient, also allows e±cient motion estimation by constraining the search process to moving macro-blocks only. The encoders PSNR is degraded by 2dB com- pared to H.264/AVC inter for such scenarios, whilst requiring only 5% of the execution time. The computational complexity of our approach is comparable to that of the DISCOVER codec which is the state of the art low complexity distributed video coding. The proposed method ¯nds blocks with moving edge blocks and processes only selected blocks. The approach is particularly suited to surveillance type scenarios with a static camera

Insignificant shadow detection for video segmentation

To prevent moving cast shadows from being misunderstood as part of moving objects in change detection based video segmentation, this paper proposes a novel approach to the cast shadow detection based on the edge and region information in multiple frames. First, an initial change detection mask containing moving objects and cast shadows is obtained. Then a Canny edge map is generated. After that, the shadow region is detected and removed through multiframe integration, edge matching, and region growing. Finally, a post processing procedure is used to eliminate noise and tune the boundaries of the objects. Our approach can be used for video segmentation in indoor environment. The experimental results demonstrate its good performance

Edge-region grouping in figure-ground organization and depth perception.

Edge-region grouping (ERG) is proposed as a unifying and previously unrecognized class of relational information that influences figure-ground organization and perceived depth across an edge. ERG occurs when the edge between two regions is differentially grouped with one region based on classic principles of similarity grouping. The ERG hypothesis predicts that the grouped side will tend to be perceived as the closer, figural region. Six experiments are reported that test the predictions of the ERG hypothesis for 6 similarity-based factors: common fate, blur similarity, color similarity, orientation similarity, proximity, and flicker synchrony. All 6 factors produce the predicted effects, although to different degrees. In a 7th experiment, the strengths of these figural/depth effects were found to correlate highly with the strength of explicit grouping ratings of the same visual displays. The relations of ERG to prior results in the literature are discussed, and possible reasons for ERG-based figural/depth effects are considered. We argue that grouping processes mediate at least some of the effects we report here, although ecological explanations are also likely to be relevant in the majority of cases

Aerial moving target detection based on motion vector field analysis

An efficient automatic detection strategy for aerial moving targets in airborne forward-looking infrared (FLIR) imagery is presented in this paper. Airborne cameras induce a global motion over all objects in the image, that invalidates motion-based segmentation techniques for static cameras. To overcome this drawback, previous works compensate the camera ego-motion. However, this approach is too much dependent on the quality of the ego-motion compensation, tending towards an over-detection. In this work, the proposed strategy estimates a robust motion vector field, free of erroneous vectors. Motion vectors are classified into different independent moving objects, corresponding to background objects and aerial targets. The aerial targets are directly segmented using their associated motion vectors. This detection strategy has a low computational cost, since no compensation process or motion-based technique needs to be applied. Excellent results have been obtained over real FLIR sequences

General Relationship Between the Entanglement Spectrum and the Edge State Spectrum of Topological Quantum States

We consider (2+1)-dimensional topological quantum states which possess edge states described by a chiral (1+1)-dimensional Conformal Field Theory (CFT), such as e.g. a general quantum Hall state. We demonstrate that for such states the reduced density matrix of a finite spatial region of the gapped topological state is a thermal density matrix of the chiral edge state CFT which would appear at the spatial boundary of that region. We obtain this result by applying a physical instantaneous cut to the gapped system, and by viewing the cutting process as a sudden "quantum quench" into a CFT, using the tools of boundary conformal field theory. We thus provide a demonstration of the observation made by Li and Haldane about the relationship between the entanglement spectrum and the spectrum of a physical edge state.Comment: 7 pages, 2 figures. A presentation of this work can be found in the following talk at KITP: http://online.itp.ucsb.edu/online/compqcm10/qi