Cut Detection Research Articles

Remote acoustic detection of cuts in a vibrating plate with stochastic input forcing in a reverberant environment.

A mechanical structure subject to vibratory forcing will often radiate sound. When remotely recorded, this sound depends on the vibratory forcing, the structure's frequency response function, and the structure-to-receiver acoustic propagation. Thus, successful remote acoustic detection of changes in a structure's vibration response between baseline and subsequent test recordings may require compensation for possible baseline-to-test changes in vibratory forcing and acoustic propagation. Compensation schemes for unknown structural forcing in an unknown reverberant environment that allow such remote detection are described here and found to be successful when the random forcing has a consistent power spectrum and the structure-radiated sound is recorded with an array of receivers. In particular, experimental results are presented for remote acoustic detection of 13-76 mm cuts in a vibrating 0.30-m-square by 3-mm-thick edge-clamped aluminum plate subject to 0.1-2 kHz base excitation in a reverberant laboratory. Radiated sound from the plate is recorded remotely with a 15-element microphone array and processed with the synthetic time reversal blind deconvolution algorithm to compensate for unknown reverberation. Cut detection success is compared for frequency-sweep and random-input forcing when this forcing is known and unknown, and when there are plate-to-array geometric changes between the baseline and test measurements.

Damage detection in carbon fiber–reinforced polymer composite via electrical resistance tomography with Gaussian anisotropic regularization

Electrical resistance tomography is a method for sensing the spatial distribution of electrical conductivity. Therefore, this type of tomography is suitable for sensing damages, which affect electrical conductivity. The utilization of resistance tomography for the structural health monitoring of carbon fiber–reinforced polymer composites is questionable owing to its low spatial resolution and the strong anisotropy of carbon fiber–reinforced polymer composites. This article deals with the employment of resistance tomography with regularization based on a Gaussian anisotropic smoothing filter for the detection of cuts. The advantages of the filter are shown through the image reconstruction of rectangular composite specimens with three different laminate stacking sequences. The cuts are implemented by a milled groove. Visual comparison of the images shows a substantial improvement in the shape reconstruction ability. In addition to visual comparison, the image reconstructions are assessed in terms of the reconstruction error and cross-correlation.

Optimize x265 Rate Control: An Exploration of Lookahead in Frame Bit Allocation and Slice Type Decision.

To improve the Rate-Distortion (R-D) quality, x265 rate-control made a variety vital decisions, such as scene cut detection, slice type decision, and coding-unit quantization parameter (QP) offsets, leveraging on lookahead to evaluate the information propagation through the current and the near future consecutive frames. However, as the frame base QP that dominates the bit amount allocated to one frame was only determined by the long-term complexity history in the original algorithm, the frame bit allocation became insensitive to the recent scene changes with the growth of coding time. In addition, the specified threshold in slice type decision, which was compared with the estimated frame coding costs to detect the B-type slice, did not consider the impacts of quantization. The aforementioned irrational elements degraded the rate accuracy and the R-D performance of x265. In this paper, the frame base QP is determined with not only the coding complexity history, but also the complexity changes and the data dependencies between the current and the near future pictures by exploring lookahead. Moreover, the quantization scale is introduced to the threshold specification in slice type decision, which identifies more pictures as B-type properly when increasing QP. The proposed algorithms were conducted in x265 version 2.4. Experiments revealed that, under the default preset (-preset medium), 0.617dB and up to 1.705dB BDPSNR quality gains were achieved, while saving the encoding time by 1.13% and improving the rate accuracy by 4.2% on average.

Motion and illumination defiant cut detection based on Weber features

The spontaneous proliferation of video data necessitates implementing hierarchical structures for various content management applications. Temporal video segmentation is the key towards such management. To address the problem of temporal segmentation, the current communication exploits the concept of psychological behaviour of the human visual system. Towards this goal an abrupt cut detection scheme has been proposed based on Weber's law which provides a strong spatial correlation among the neighbouring pixels. Thus, the authors provide a robust and unique solution for abrupt shot boundary detection when the frames are affected partially or fully by flashlight, fire and flicker, high motion associated with an object or camera. Further, they have devised a model for generating an automatic threshold, taking into account the statistics of the feature vector which quadrates itself with the variation in the contents of the video. The effectiveness of the proposed framework is validated by exhaustive comparison with few contemporary and recent approaches by using benchmark datasets TRECVID 2001, TRECVID 2002, TRECVID 2007 and some publicly available videos. The results obtained give credence to the remarkable improvement in the performance while preserving a good trade-off between missed hits and false hits as compared to the state-of-the-art methods.

Generative Model Based Video Shot Boundary Detection for Automated Surveillance

Video shot boundary detection (SBD) or video cut detection is one of the fundamental processes of video-processing with respect to semantic understanding, contextual information accumulation, labeling, content-based information retrieval and many more applications, such as video surveillance and monitoring. In this work, the authors have proposed a generative-model based framework for detecting shot boundaries in between the frames of a video segment. To generate a model of shot-boundaries, the authors have applied the concepts of Support Vector Machine to estimate the distance between any two images, and then, have generated a Gaussian Mixture Model from the estimated distances. Next, a Bayesian Estimation process checks the presence of boundaries in between the images by exploiting the Gaussian Mixture-based boundary model. Further, the authors have used the principles of Compressive Sensing to reduce the overhead of boundary detection process without losing of important information.

Identifying Partitions in Wireless Sensor Network

Wireless sensor networks, consists of a group of tiny nodes, which are powered by small size batteries, which can get failed very easily. The failure of a single node may lead to the failure of an entire network in the following way. If a particular node is unaware of the failed situation of its neighbor node, it simply forwards the packet again and again as it will not receive any acknowledgment. This message passing merely wastes the precious energy of the node, which leads to its failure. This process continues which leads to the failure of the entire network. It is crucial, to identify the node which is failed, as and when it happens and to reconnect the network. In this paper, a hop count based cut detection algorithm is proposed to detect the failure of the nodes and, mobile nodes are used to reconnect the partitioned network. In HCCD at each hop, every node select the node with minimum hop count and maximum link cost, thereby the worst node can be identified as cut node and this cut can be identified before the network actually fails. Experiment results shows that hop count based cut detection outperforms the traditional distributed cut detection algorithm and reconnection using mobile nodes avoids data loss.

A video hard cut detection using multifractal features

Efficient management of video sequences is based on adequate video content description. This description can be used for various purposes in different applications, telecommunication services, video and multimedia systems. Video hard cut detection represents the foundation of temporal video segmentation. In this paper, a new video hard cut detection methodology is proposed using multifractal features. Transition between two shots can be described as color and texture differences within a decoded video sequence. In the proposed methodology we formed specific structures by measuring color differences between frames. The formed structures are used for hard cut candidate detection. This is followed by multifractal representation of texture changes by Holder exponents. The proposed methodology achieves high performance using more than 750,000 frames, extracted from forty different video sequences, classified by four well known genre groups. Moreover, the proposed hard cut detection achieves high performance regardless of high level video production or complex non-linear editing for different genre groups. This is confirmed by comparison between the proposed methodology and other recent work on hard cut detection.

Relative Flow Estimates for Shot Boundary Detection

This paper proposes a simple approach based on Relative Flow Estimates (RFE) for shot cut detection. The property of Relative flow estimates can be used for abrupt cut detection and a correction mechanism for gradual camera-shot transition detection (e.g., fade-in and fade-out, dissolves, wipes). The exacted feature vector in each frame can be mapped into a 3-D space along the continuous time axis, and these feature data can be treated as a virtually constructed pipe with fluid flowing in the 3-D axis. Compared with existing approaches, the new RFE-based algorithm can directly detect shot cut. A wide range of test videos are used to evaluate the performance of the proposed method. The experimental results show that the new scheme can produce promising results.

COMPARISON OF 3D POINT CLOUDS FROM AERIAL STEREO IMAGES AND LIDAR FOR FOREST CHANGE DETECTION

Abstract. This study compares performance of aerial image based point clouds (IPCs) and light detection and ranging (LiDAR) based point clouds in detection of thinnings and clear cuts in forests. IPCs are an appealing method to update forest resource data, because of their accuracy in forest height estimation and cost-efficiency of aerial image acquisition. We predicted forest changes over a period of three years by creating difference layers that displayed the difference in height or volume between the initial and subsequent time points. Both IPCs and LiDAR data were used in this process. The IPCs were constructed with the Semi-Global Matching (SGM) algorithm. Difference layers were constructed by calculating differences in fitted height or volume models or in canopy height models (CHMs) from both time points. The LiDAR-derived digital terrain model (DTM) was used to scale heights to above ground level. The study area was classified in logistic regression into the categories ClearCut, Thinning or NoChange with the values from the difference layers. We compared the predicted changes with the true changes verified in the field, and obtained at best a classification accuracy for clear cuts 93.1 % with IPCs and 91.7 % with LiDAR data. However, a classification accuracy for thinnings was only 8.0 % with IPCs. With LiDAR data 41.4 % of thinnings were detected. In conclusion, the LiDAR data proved to be more accurate method to predict the minor changes in forests than IPCs, but both methods are useful in detection of major changes.

Textile sensors for stab and cut detection

Manufacturers are aiming for more flexible and lightweight protective clothing to increase wearing comfort. A cardigan with a knitted stab-resistant inlay and an alarm system is presented. The stab-resistant inlay is based on a multilayer ultra-high molecular weight poly ethylene (UHMW-PE) fabric. Stab resistance was evaluated according to the standard of the Association of Test Laboratories for Bullet, Stab or Pike Resistant Materials and Construction Standard (VPAM 2011). Furthermore sensors for the detection of cuts and pressure were integrated. Both sensors can trigger alarms if the wearer is attacked. Normal pressure occurring through leaning on a wall or sitting is filtered out and does not trigger an alarm.

Dual-dissimilarity measure-based statistical video cut detection

Video cut detection is an essential process of temporal continuity-based video applications such as video segmentation, video retargeting, and frame rate up-conversion. The performance of these applications highly depends on the performance of cut detection. This paper proposes an effective and low-complexity approach for detecting video cuts. The proposed method uses two simple dissimilarity measures for video cut detection: inter-frame luminance variation and temporal variation of inter-frame variations over several frames. The first is used to detect abrupt changes, and the second is used to reduce the influence of disturbances, e.g., object or camera motion. The proposed method is comprised of the following three steps. First, it computes the two dissimilarity measures. Then, it combines them using Bayesian estimation and linear regression. Finally, it decides on the possibility of cuts using the combined dissimilarity measure. Experimental results show that the average F1 score of the proposed method was up to 0.252 (37.0%) higher than those of the benchmark methods. Moreover, the algorithmic simplicity of the proposed method reduced the average computation time per pixel by up to 99.8%, when compared with state-of-the-art methods. Thus, the proposed method is superior to existing methods in terms of computational complexity and detection accuracy.

An effective graph‐theoretic approach towards simultaneous detection of fault(s) and cut(s) in wireless sensor networks

SummaryA failed sensor node partitions a wireless sensor network (WSN) into 2 or more disjoint components, which is called as a cut in the network. The cut detection has been considered as a very challenging problem in the WSN research. In this paper, we propose a graph‐theoretic distributed protocol to detect simultaneously the faults and cuts in the WSN. The proposed approach could be accomplished mainly in 3 phases, such that initialization phase, fault detection phase, and a cut detection phase. The protocol is an iterative method where at every time iteration, the node updates its state to calculate the potential factor. We introduced 2 terminologies such as a safe zone or cut zone of the network. The proposed method has been evaluated regarding various performance evaluation measures by implementing the same in the network simulator NS–2.35. The obtained results show that the proposed graph‐theoretic approach is simple yet very powerful for the intended tasks.

Viral Subtypes, Coreceptor Usage and Phylogenetic Relationships of Hiv-1 Isolates in Discordant Positive and Concordant Couples

There are various cardiac biomarkers available for diagnosis and stratification of patients with acute coronary syndrome but only few are cardiospecific and sensitive. Troponins are protein molecules that are part of cardiac and skeletal muscle. Smooth muscle cells do not contain troponins. There are three subunits of troponin T, I and C subunits. Cardiac troponins are known to increase on myocardial cell damage leading to myocardial necrosis. The kinetic pattern of release of troponin is known. The technological advancements in Immunoassay has led to improvement in the limit of detection, (LoD) Limit of quantitation (LoQ) and cut off detection limits. There are decreases in false positive cases due to antihuman antibodies use of sandwich fifth generation Troponin T immunoassay. Recently the troponin T fifth generation by (Roche diagnostics) is approved by US-FDA. The cutoffs detections and positive 99th percentile of reference population cutoffs has to be established by verification of manufacturers reference cutoff s limits. The delta change value after serial measurements of suspected patients with symptoms of AMI leads to diagnosis.

Analysis of multitemporal aerial images for fenyőfő Forest change detection

This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.

Match-Action: The Role of Motion and Audio in Creating Global Change Blindness in Film

An everyday example of change blindness is our difficulty to detect cuts in an edited moving-image. Edit blindness (Smith & Henderson, 2008) is created by adhering to the continuity editing conventions of Hollywood, for example, coinciding a cut with a sudden onset of motion (match-action). In this study, we isolated the roles motion and audio play in limiting awareness of match-action cuts by removing motion before and/or after cuts in existing Hollywood film clips and presenting the clips with or without the original soundtrack whilst participants tried to detect cuts. Removing post-cut motion significantly decreased cut detection time and the probability of missing the cut. By comparison, removing pre-cut motion had no effect suggesting, contrary to the editing literature, that the onset of motion before a cut may not be as critical for creating edit blindness as the motion after a cut. Analysis of eye movements indicated that viewers reoriented less to new content across intact match-action cuts than shots with motion removed. Audio played a surprisingly large part in creating edit blindness with edit blindness mostly disappearing without audio. These results extend film editor intuitions and are discussed in the context of the Attentional Theory of Cinematic Continuity (Smith, 2012a).

The quantitative description of gas-cut degree in deepwater drilling

Abstract Through the analysis of gas-cut features in deepwater drilling and shortages of existing gas-cut detection methods, the feasibility of early detection of gas cut at the bottom of riser was demonstrated, and a method was proposed for quantitative description of gas-cut degree in deepwater drilling based on ultrasonic monitoring at the bottom of riser. The problems of Doppler ultrasound gas-cut detection method was analyzed and the experimental device of gas-cut monitoring at the bottom of riser based on the ultrasonic transmission was built, which was used to analyze the sound attenuation characteristics under different conditions of void fraction. The solutions for using ultrasound to monitor gas-cut situation at the bottom of riser was proposed. Combined with the gas-liquid two-phase model of wellbore annulus in deepwater drilling and the formation pressure prediction method with credibility, the inverse calculation method of gas-cut degree in wellbore was established, which was based on the monitoring data of gas cut at the bottom section of riser. This method could detect the gas cut about four minutes in advance compared with conventional methods, and the gas cut occurring moment, the time left for gas to reach the wellhead, the total overflow rate at any moment, and the void fraction in different depth could be accurately determined based on the acoustic response data of the bottom of riser.

Piecewise-planar reconstruction using two views

The article describes a reconstruction pipeline that generates piecewise-planar models of man-made environments using two calibrated views. The 3D space is sampled by a set of virtual cut planes that intersect the baseline of the stereo rig and implicitly define possible pixel correspondences across views. The likelihood of these correspondences being true matches is measured using signal symmetry analysis [1], which enables to obtain profile contours of the 3D scene that become lines whenever the virtual cut planes intersect planar surfaces. The detection and estimation of these lines cuts is formulated as a global optimization problem over the symmetry matching cost, and pairs of reconstructed lines are used to generate plane hypotheses that serve as input to PEARL clustering [2]. The PEARL algorithm alternates between a discrete optimization step, which merges planar surface hypotheses and discards detections with poor support, and a continuous optimization step, which refines the plane poses taking into account surface slant. The pipeline outputs an accurate semi-dense Piecewise-Planar Reconstruction of the 3D scene. In addition, the input images can be segmented into piecewise-planar regions using a standard labeling formulation for assigning pixels to plane detections. Extensive experiments with both indoor and outdoor stereo pairs show significant improvements over state-of-the-art methods with respect to accuracy and robustness.

Parametric Study of Defect Detection in Pipes with Bend Using Guided Ultrasonic Waves

The propagation behaviour of guided ultrasonic waves in a steel pipe with welded bend is studied by finite element simulation. The effectiveness of the longitudinal L(0,2) and torsional T(0,1) guided waves in detecting circumferential cut near the weld is investigated. In order to identify the presence of the defect, the reflection strength due to the cut is studied. The geometry of the weld is constructed based on common V-bevel butt joints and the anisotropy of the 316L stainless steel weld is included to correctly predict the scattering of ultrasonic waves. The finite element model is built to allow high accuracy. Detection of small circumferential cut (up to 60° circumferential extent) can be achieved with longitudinal L(0,2) mode. Detection of moderate to large circumferential cut can be achieved by torsional T(0,1) or longitudinal L(0,2) modes, with T(0,1) mode preferred due to its less mode conversion to higher order modes.

Multi-video processing applications on FPGA

With the increasing needs of processing power in video and image processing for advanced media and communication applications, it is mandatory to go further than the software implementation to provide generic, real time, low cost and high performance hardware platforms. In this paper, we present a re-configurable, hardware platform for video and image processing. The proposed system uses the benefits of field programmable gate array FPGA to attain this objective. In this context, a prototype system is developed based on the Xilinx Virtex-5 FPGA with the integration of embedded processor, embedded memory, multi-port memory controller MPMC, standard interfaces, and different other resources. Our system includes different functional modules: video cut detection, video zoom-in and zoom-out. This provides the flexibility of using this system as a general video processing platform according to different application requirements. The final system utilises ∼16% of logic resource and 20% of on chip memory.

Distributed Cut Detection in Wireless SensorNetwork

A wireless sensor network (WSN) is a deployment of a large number of small, inexpensive, selfpowered devices that can sense , compute, and communicate with other devices for the purpose of gathering local information about a physical environment. We propose a distributed algorithm to detect “CUT“ in Wireless sensor networks, that mean the failure of any single node or set of node that separates the network in to two or more components. Algorithm is iterative and asynchronous i.e every node is communicate only those node that are in the rang. Simulation result show that this algorithm leads to very good detection performance compared to existing techniques.