Edge-finding Algorithms Research Articles

Manifestation of internal waves in the Southern Caspian Sea using satellite imagery

Iran's South Caspian coast is an important agricultural hotspot and densely populated area that attracts about 20 million domestic tourists in summer. Therefore, not only the coastal area ecosystem of the South Caspian Sea (SCS) but also their marine ecosystem is exposed to different environmental pollution. The ecosystem of the SCS especially in the onshore area strongly affected by Internal Waves (IWs) dynamics. IWs can capture, concentrate and transport, floating plastic debris, larvae, contaminants, and toxic pollutants in this basin. Therefore, detecting and zoning the SCS for IWs is critical to the management and protection of this enclosed basin. Measured data obtained from CTD and satellite imagery archives from Landsat 7, 8, and Sentinel-2 have been used to analyze and manifest IWs. Analysis and comparison of different satellite images reveal that the maximum wavelength of the IWs packet was about 400 m with a crest length of 18,000 m. However, the minimum packet had a wavelength of about 20 m with a crest length of 360 m. Based on the occurrence of IWs extracted by edge-finding algorithms on satellite images, the SCS can be divided into six original zones. Four zones of them located near the coastal line where freshwater rivers discharge to the sea in the rainy season and two other zones are in the deep water, which form under the dominant sea surface wind regime and sharp changing of bathymetry.

Rapid shipboard measurement of net-collected marine microplastic polymer types using near-infrared hyperspectral imaging

Isolation and detection of microplastics (MP) in marine samples is extremely cost- and labor-intensive, limiting the speed and amount of data that can be collected. In the current work, we describe rapid measurement of net-collected MPs (net mesh size 300 µm) using a benchtop near-infrared hyperspectral imaging system during a research expedition to the subtropical North Atlantic gyre. Suspected plastic particles were identified microscopically and mounted on a black adhesive background. Particles were imaged with a Specim FX17 near-infrared linescan camera and a motorized stage. A particle mapping procedure was built on existing edge-finding algorithms and a polymer identification method developed using spectra from virgin polymer reference materials. This preliminary work focused on polyethylene, polypropylene, and polystyrene as they are less dense than seawater and therefore likely to be found floating in the open ocean. A total of 27 net tows sampled 2534 suspected MP particles that were imaged and analyzed at sea. Approximately 77.1% of particles were identified as polyethylene, followed by polypropylene (9.2%). A small fraction of polystyrene was detected only at one station. Approximately 13.6% of particles were either other plastic polymers or were natural materials visually misidentified as plastics. Particle size distributions for PE and PP particles with a length greater than 1 mm followed an approximate power law relationship with abundance. This method allowed at-sea, near real-time identification of MP polymer types and particle dimensions, and shows great promise for rapid field measurements of microplastics in net-collected samples.

Evidence for a transition in the cortical membranes of Paramecium

Ever since the pioneering studies in the 1960s and 70s, the importance of order transitions for cell membrane functions has remained a matter of debate. Recently, it has been proposed that the nonlinear stimulus-response curve of excitable cells, which manifests in all-or-none pulses (action potentials (AP)), is due to a transition in the cell membrane. Indeed, evidence for transitions has accumulated in plant cells and neurons, but studies with other excitable cells are expedient in order to show if this finding is of a general nature. Herein, we investigated intact, motile specimens of the “swimming neuron” Paramecium. The cellular membranes were labelled with the solvatochromic fluorophores LAURDAN or Di-4-ANEPPDHQ. Subsequently, a cell was trapped in a microfluidic channel and investigated by fluorescence spectroscopy. The generalized polarization (GP) of the fluorescence emission from cell cortical membranes (probably plasma and alveolar membranes) was extracted by an edge-finding algorithm. The thermo-optical state diagram, i.e. the dependence of GP on temperature, exhibited clear indications for a reversible transition. This transition had a width of ~10–15 °C and a midpoint that was located ~4 °C below the growth temperature. The state diagrams with LAURDAN and Di-4-ANEPPDHQ had widely identical characteristics. These results suggested that the cortical membranes of Paramecium reside in an order transition regime under physiological growth conditions. Based on these findings, membrane potential fluctuations, spontaneous depolarizing spikes, and thermal excitation of Paramecium was interpreted.

Convolutional Neural Network Based Brain Tumor Classification Using Robust Background Saliency Detection

To perceive the tumors found in brain and their treatment, experts manually note and identify different Regions of Interest (ROI). To overcome the faults and divergences during this state, automated analysis is performed. A unique technique is used to classify the tumor section of the brain from an MRI is proposed using saliency-focused image depiction and optimization in classification based on CNN. Primarily, the MRI images are pre-processed using the Canny Edge Finding algorithm and then those images are represented as saliency driven based on Robust Background Saliency Detection (RBD). Followed by the abstraction of features then classifying the image is performed using CNN along with ADAM optimization. The implementation is accomplished, and the results are analyzed, showing that it outperforms previous techniques.

A method to extract image noise level from patient images in CT.

Image quality in computed tomography (CT) is usually not quantified in real time from patient scans. Rather, phantom scans are employed to measure the contrast, noise, and spatial resolution properties of a given system. This approach, however, is not ideal because many factors are difficult to represent using phantoms like variations in patient size, composition, and position within the gantry. Several methods for measuring the noise found within patient scans have been proposed. All of these methods rely on segmenting out relatively uniform regions within the patient in order to differentiate between morphological variations and pixel differences due to photon noise. In order to avoid this segmentation step, we propose to analyze the noise signal in the air surrounding the patient. We will demonstrate that the air signal surrounding the patient acts as a surrogate for the noise within the contours of the patient. Our work builds off the global noise index (GNI) method. In the GNI method, adjacent axial CT image slices are subtracted to remove the majority of the morphological variations in the data. Remaining morphological variations are removed with an edge-finding algorithm. Then the image is divided up into small regions of interest (ROI) and the pixel standard deviation is computed for each ROI. Only those ROIs not containing bone or air are then used to make a histogram of the standard deviation within the image. The mode of this histogram is referred to as the GNI. We refer to this as the traditional GNI (tradGNI). Our modification to this workflow is to apply this metric to just the air signal surrounding the patient. We evaluate the correlation between using the air signal and the in-phantom metric value for titration over: dose level, image slice thickness, kernel sharpness, iterative reconstruction level, model based iterative reconstruction, reconstruction field of view, and reconstruction interval. 373 patient abdomen pelvis exams were collected and the air based noise estimation metrics applied. Liver standard deviation values were measured on 40 of the patients and correlated with air GNI calculations. Our results show excellent linear correlation (R2 > 0.99) between the tradGNI being applied inside and outside of a phantom object. Our results are also shown to still be predictive of the noise under all scan parameters studied, including iterative and model based reconstruction. Fits of tradGNI versus dose level exhibited the expected square root dependence. Air based GNI metrics were predictive of human patient noise level and also correlated with manual liver standard deviation measurement (R2 = 0.73). Our results demonstrate the signal in the air surrounding an imaging object can accurately be used as a surrogate for the image noise within the object. Our method should enable faster and more robust patient specific image quality assessment due to the lack of the need to segment noise from morphological variations within a patient.

Approaches for image segmentation applied to food

For the task of image recognition, it is unpractical to process an image as a whole, since it is highly inefficient and most of the times challenging for the users. Image segmentation techniques are used to divide one image into multiple regions or clusters, it consists in assigning regions to each of the image pixels using different metrics such as pixel colour value, gray-scale intensity, edge finding algorithms, among others. The most diverse image segmentation algorithms have already been proposed and are currently used. However, there are three main categories of segmentation to which the existing algorithms can be assigned and we are going to discuss in this survey: region-based segmentation, data clustering, and edge-based segmentation. With this document, we study diverse commonly used segmentation algorithms, analyse their behaviour as well as their benefits and disadvantages, and present comparative experimental results when applied to a test image.

Measurement and characterization of fully transient diesel fuel jet processes in an optical engine with production injectors

The effects of transient rate-of-injection profiles on high-pressure diesel fuel jets have been studied in an optically accessible internal combustion engine. High-speed optical imaging measurements were applied over a range of ambient conditions, fuel types, and injection parameters. This paper demonstrates that during the early part of the injection, while the liquid core is disintegrating, the penetration is functionally linked to the inviscid orifice exit velocity up until a downstream distance hypothesized to be the jet breakup length. The jets then transitioned to a mixing dominated penetration behavior afterward. Therefore, for cases that exhibit transient rate-of-injection profiles, quasi-steady penetration analytical solutions for penetration have poor agreement with the empirical data. The development of an adaptive edgefinding algorithm for accurately detecting jets in engines is detailed. These findings indicate that empirical correlations widely used throughout the engine community for estimating jet penetration do not accurately represent actual injection parameters under transient conditions.

Wicking behavior of fabrics described by simultaneous acquiring the images of the wet region and monitoring the liquid weight

An experimental study on the radial spreading of the liquid from a virtually infinite reservoir onto a horizontal fabric sample was performed using a simple setup which is presented in two variants: One variant (the simplest) collects the images of the wet spot during the radial outward wicking and the other variant collects the images simultaneously with the monitoring of the weight decrease of the liquid reservoir. We notice that recording with a webcam gives advantages in the subsequent data processing. Afterward, the resulting image series were processed with routines developed in LabVIEW to determine the area of the wet spot. The programs are better adapted to the inhomogeneous and anisotropic structure specific to textiles than the existent edge-finding algorithms. The time dependence of the wet area provides information about the wicking kinetics and further, by modeling the data, to the possible mechanism. The experiments were performed using solutions of red (rhodamin 6B) or blue (brilliant blue E133) dyes in linen and polyester samples differing besides the chemical structure in the roughness of their surfaces as well. The data allow an easy comparison between the textile behavior. Determination of the mass loss of the test liquid might be useful especially for the colored fabrics. The infinite reservoir case is compared with that of the finite reservoir.

Bending Modulus Dictates GUV Response to Stress

We investigated the dynamic response of membranes with different bending moduli to stress, which phase diagrams for vesicles conformations at equilibrium cannot predict. We used melittin to systematically modify the bending modulus of 1,2-Dioleoyl-sn-glycero-3-phosphocholine (DOPC) phospholipid membrane. The bending moduli of DOPC giant unilamellar vesicles (GUVs) at different peptide-to-lipid (P/L) ratios were estimated with contour fluctuation analysis, for which we developed an edge finding algorithm for fluorescence images. We saw that the bending modulus decreased with increasing P/L before pore formation, but the trend was reversed after pore formation. When GUVs of different bending moduli were subjected to similar stress, the morphology distributions of large numbers of vesicles at equilibrium were different. The difference reflects the greater volume loss of vesicles with lower bending modulus, for which higher tension can build up in the membrane when vesicles deform under stress. Beyond a threshold tension, vesicles form transient pores through which contents can flow out to release the tension.

Unconstrained approach for isolating individual trees using high-resolution aerial imagery

This study outlines an algorithm that can be used for individual tree detection and crown delineation; it was applied to coniferous forest using aerial imagery. This article explains the assumptions and processes involved in the algorithm, presents the results of the applications, and discusses possible limitations. The algorithm, which adopts contextual analysis that excludes the need to specify window size, was applied to detect and delineate individual trees based on morphological and reflective characteristics. The preprocessing steps included suppression of the non-coniferous area (i.e. non-forest and leaf-off deciduous forest) and the creation of appropriately smoothed imagery using an optimal smoothing level based on accuracy index (AI); thereafter, unconstrained directional peak- and edge-finding algorithms were processed separately. To assess the tree detection and crown delineation processes, the results of the algorithms were evaluated carefully against visually interpreted crowns in six square plots using several statistical measures based on tree top correspondence, positional difference of tree top, directional crown width, and crown area assessment. The average tree top correspondence had an AI of 88.83%. The positional difference between detected and visually interpreted tree tops was measured and its average was 0.6 m. For our 0.5 m/pixel aerial imagery, the average root mean square error (RMSE) of crown width in six sample plots was found to be 2.8 m, and crown area estimation resulted in RMSE of approximately 9.23 m2 (23.25%). In general, this study highlights the potentiality of the proposed algorithm to efficiently and automatically acquire forest information such as tree numbers, crown width, and crown area.

Imaging Ejecta and Debris Cloud Behavior Using Laser Side-lighting

The Caltech Small Particle Hypervelocity Impact Range (SPHIR Facility) utilizes a two-stage, light gas gun to accelerate Nylon 6/6 right cylinders (d = 1.8mm, L/D=1, 5.5mg) and spheres (d = 1.8mm, 3.6mg) to impact speeds of 5km/s and above. The projectiles impact aluminum 6061-T6 plate targets. An optical technique was employed to produce images of the hypervelocity impact event with short exposure times (20ns) and short inter-frame times (<1μs). The technique uses coherent illumination, orthogonal to the projectile flight direction, to provide a series of shadowgraph images of the impact on the target. An expanded beam from a 532nm continuous wave laser is used as the illumination source. The beam is expanded to illuminate a 10cm diameter area and is then directed to a gated, intensified high-speed CCD camera. The front ejecta and debris clouds created behind the target are simultaneously imaged with this system. An edge-finding algorithm has been developed to provide a consistent method for identifying the position of the debris-front in sequential images. This technique enables a regular method to investigate the debris cloud evolution and to characterize its asymmetrical features. Furthermore, with the Laser Side-lighting system atmospheric waves emanating from the impact site are also visible. Increasing the atmospheric pressure in the target chamber (above the nominal 1.5 Torr) significantly increases the observable features of these shock waves. The behaviour of these waves provides an improved understanding of the temporal sequence of the impact phenomena.

A quadratic extended edge-finding filtering algorithm for cumulative resource constraints

Edge-finding, extended edge-finding, not-first/not-last and energetic reasoning are well-known filtering rules used in constraint-based scheduling problems for propagating constraints over disjunctive and cumulative resources. In practice, these filtering algorithms frequently form part of a sequence to form a more powerful propagator, thereby helping to reduce search tree size. In this paper, we propose a sound O(n2) extended edge-finding algorithm for cumulative resources, where n is the number of tasks sharing the resource. This algorithm uses the notion of minimum slack to detect when extended edge-finding justifies a strengthening of a domain, and it is more efficacious when executed on a domain already at the fix point of standard edge-finding. Previously, the best known complexity for filtering extended edge-finding on cumulative resources was O(kn2) (where k is the number of distinct capacity requirements). Experimental results on resource constrained scheduling benchmarks confirm that the new algorithm outperforms previous extended edge-finding algorithms, and sometimes results in better performance than standard edge-finding alone. Furthermore, we show that our method is competitive with the current state-of-the-art in edge-finding-based algorithms.

Energetic Extended Edge Finding Filtering Algorithm for Cumulative Resource Constraints

Edge-finding and energetic reasoning are well known filtering rules used in constraint based disjunctive and cumulative scheduling during the propagation of the resource constraint. In practice, however, edge-finding is most used (because it has a low running time complexity) than the energetic reasoning which needs O（n3） time-intervals to be considered (where n is the number of tasks). In order to reduce the number of time-intervals in the energetic reasoning, the maximum density and the minimum slack notions are used as criteria to select the time-intervals. The paper proposes a new filtering algorithm for cumulative resource constraint, and titled energetic extended edge finder of complexity O（n3）. The new algorithm is a hybridization of extended edge-finding and energetic reasoning: more powerful than the extended edge-finding and faster than the energetic reasoning. It is proven that the new algorithm subsumes the extended edge-finding algorithm. Results on Resource Constrained Project Scheduling Problems (RCPSP) from BL set and PSPLib librairies are reported. These results show that in practice the new algorithm is a good trade-off between the filtering power and the running time on instances where the number of tasks is less than 30.

Edge Detection using Directional Filter Bank

Finding edges in digital images is an essential and important task in many imaging applications. This paper describes an edge detection using multi scale Directional Filter Bank (DFB). This method tries to solve two difficulties that edge finding algorithms must face: limited directions and combining the detected edges at different scales. The directional responses of DFB that represent the edge information can be used for edge detection. The steerable and scaled DFB has been presented to obtain directional along with scaled information. From the DFB based image decomposition, the scaled information is combined by scale multiplication. Finally, to evaluate edge detector performance the sensitivity, specificity, accuracy and Figure of merit ‘F’ parameters are used to compare with classical methods and the proposed approach provides better performance.

Three-Dimensional Wallmapping Using Xradia with Distortion Correction

The inertial confinement fusion program requires the uniformity of multilayered samples to be measured to high accuracy. We currently use a reflection spectroscopy tool to measure optically transparent shells with no more than two layers. The method cannot measure opaque samples such as beryllium shells, low-reflection samples such as foam shells, or any shells with more than two layers such as National Ignition Facility specification Ge-CH shells. We also use a white-light interferometer to measure transparent samples with multiple layers, but only at the North/South Poles for a given orientation. To complement these existing tools, we developed an X-ray technique based on a commercial X-ray microscope (Xradia MicroXCT). MicroXCT is capable of providing high-contrast, high-resolution images and allows the samples to be precision aligned and angular indexed. Dimension accuracy is achieved through the calibration of the projection magnification and the lens distortion. From each X-ray image, a wall thickness trace along the great circle is obtained by converting Cartesian coordinates into cylindrical coordinates, and edge-finding algorithms are developed for a contact radiography project. Three-dimensional reconstruction and wall thickness display allow the visualization of the sample nonuniformity. The method has a 0.3 μm measurement precision and, through phase contrast calibration, can achieve 0.3 μm accuracy.

Methods for calculating the severity of demineralization on tooth surfaces from PS-OCT scans.

Several studies have demonstrated that polarization sensitive optical coherence tomography (PS-OCT) can be used to nondestructively measure the severity of subsurface demineralization in enamel and dentin. The reflectivity in the polarization state orthogonal to the initial linear polarization incident on the tissue is low at sound tissues interfaces and high in demineralized areas that strongly scatter and depolarize the light. The purpose of this study was to develop improved algorithms for assessing the depth and severity of demineralization from PS-OCT scans for use with 2D and 3D tomographic images. Subsurface caries-like lesions of increasing depth and severity were produced in adjoining windows on ten bovine enamel samples by exposure to demineralization over periods of 1 to 4 days. Each sample also had a sound window to be used as a control. PS-OCT scans were acquired for each sample and analyzed using various methods to calculate the lesion depth and area. Algorithms were developed and used to automatically detect the lesion depth and area, and calculate the volume for improved assessment of lesion severity. Both fixed-depth and automatic edge-finding algorithms were able to detect significant differences between each of the days and sound enamel. The lesion depth and mineral loss were also measured with polarized light microscopy and transverse microradiography after sectioning the teeth. Mean lesion depths ranged from 40 to 100 μm. This demonstrates the edge-finding algorithm can be used to automatically determine the depth and severity of early lesions for the rapid analysis of PS-OCT images.

Edge Finding for Cumulative Scheduling

The introduction of edge-finding techniques was a significant development in constraint-based scheduling. Today, edge finders are still the state of the art in the disjunctive case and a technique of interest in cumulative scheduling. This paper reconsiders edge-finding algorithms for cumulative scheduling and shows that Nuijten's edge finder, and its derivatives, are incomplete because they use an invalid dominance rule. We then present a correct cumulative edge finder running in time O(n2k), where n is the number of tasks and k the number of different capacity requirements of the tasks. The new algorithm is organized in two phases and first uses dynamic programming to precompute the innermost maximization in the edge-finder specification. The paper also proposes the first extended edge-finding algorithms that run in time O(n2k), improving the running time of available algorithms. Finally, the paper discusses how to speed up the algorithm in practice and how the first phase can be used to improve algorithms based on energetic reasoning.

Resolution-matched shadow maps

This article presents resolution-matched shadow maps (RMSM), a modified adaptive shadow map (ASM) algorithm, that is practical for interactive rendering of dynamic scenes. Adaptive shadow maps, which build a quadtree of shadow samples to match the projected resolution of each shadow texel in eye space, offer a robust solution to projective and perspective aliasing in shadow maps. However, their use for interactive dynamic scenes is plagued by an expensive iterative edge-finding algorithm that takes a highly variable amount of time per frame and is not guaranteed to converge to a correct solution. This article introduces a simplified algorithm that is up to ten times faster than ASMs, has more predictable performance, and delivers more accurate shadows. Our main contribution is the observation that it is more efficient to forgo the iterative refinement analysis in favor of generating all shadow texels requested by the pixels in the eye-space image. The practicality of this approach is based on the insight that, for surfaces continuously visible from the eye, adjacent eye-space pixels map to adjacent shadow texels in quadtree shadow space. This means that the number of contiguous regions of shadow texels (which can be efficiently generated with a rasterizer) is proportional to the number of continuously visible surfaces in the scene. Moreover, these regions can be coalesced to further reduce the number of render passes required to shadow an image. The secondary contribution of this paper is demonstrating the design and use of data-parallel algorithms inseparably mixed with traditional graphics programming to implement a novel interactive rendering algorithm. For the scenes described in this paper, we achieve 60--80 frames per second on static scenes and 20--60 frames per second on dynamic scenes for 512 2 and 1024 2 images with a maximum effective shadow resolution of 32,768 2 texels.

Specifying non‐uniform cusp heights as a potential aid for adaptive slicing

Most adaptive slicing implementations assume a maximum allowable cusp height which applies to the entire part. Practically speaking, however, most parts do not have uniform cusp height requirements. Some faces are required to be smooth while other faces are relatively unimportant. With a uniform cusp height implementation, users must specify the most stringent cusp height which applies to the entire part. However, with non‐uniform cusp height specifications, it is possible that further gains in adaptive slicing efficiency can be achieved. This paper presents an approach to specifying non‐uniform cusp height requirements. First, a procedure is developed which uses an edge finding algorithm to identify faces on the part. The faces are then rendered using the OpenGL graphics libraries, and the user is prompted to enter the maximum allowable cusp height for each highlighted face. Implementation details and test results are presented.

Improved approach to boundary location in two-dimensional echocardiographic images

The widespread utilisation of digital two-dimensional echocardiography has led to an increasing interest in the possibility of automated analysis of the images using this technique. For quantitative analysis of cardiac function the detection of the endocardium and epicardium is of considerable importance yet, particularly in certain key views, most conventional edge finding algorithms can be easily undermined because of the poor quality of the images and the appearance of irrelevant structures within the viewing area. The authors describe a new approach to boundary detection which, while based principally on a radial search technique, extends the conventional analysis through the addition of further contour analysis in two preprocessed images. The algorithms are described in detail and results are presented to illustrate the advantageous features of the approach proposed.