Shape Detection Research Articles

Detection of multipoint pulse waves and dynamic 3D pulse shape of the radial artery based on binocular vision theory

Background and objectivePulse signals contain a wealth of human physiological and pathological information. How to get full pulse information is especially challenging, and most of the traditional pulse sensors can only get the pulse wave of a single point. This study is aimed at developing a binocular pulse detection system and method to obtain multipoint pulse waves and dynamic three-dimensional pulse shape of the radial artery. MethodsThe proposed pulse detection approach is image-based and implemented by two steps. First, a new binocular pulse detection system is developed based on the principle of pulse feeling used in traditional Chinese medicine. Second, pulse detection is achieved based on theories and methods of binocular vision and digital image processing. In detail, the sequences of pulse images collected by the designed system as experimental data are sequentially processed by median filtering, block binarization and inversion, area filtering, centroids extraction of connected regions, to extract the pattern centroids as feature points. Then stereo matching is realized by a proposed algorithm based on Gong-shape scan detection. After multipoint spatial coordinate calculation, dynamic three-dimensional reconstruction of the thin film shape is completed by linear interpolation. And then the three-dimensional pulse shape is achieved by finding an appropriate reference time. Meanwhile, extraction of multipoint pulse waves of the radial artery is accomplished by using a suitable reference origin. The proposed method is analyzed from three aspects, which are pulse amplitude, pulse rate and pulse shape, and compared with other detection methods. ResultsAnalysis of the results shows that the values of pulse amplitude and pulse rate are consistent with the characteristics of pulse wave of the radial artery, and pulse shape can correctly present the shape of pulse in space and its change trend in time. The comparison results with the other two previously proposed methods further verify the correctness of the presented method. ConclusionsThe designed binocular pulse detection system and proposed algorithm can effectively detect pulse information. This tactile visualization-based pulse detection method has important scientific significance and broad application prospects and will promote further development of objective pulse diagnosis.

Comparative analysis of zoning approaches for recognition of Indo Aryan language using SVM classifier

Off-line text recognition is a branch of OCR. In Character recognition system, shape detection and feature mining is extremely vital part of the system. In most of the character recognition system of past researches they used zoning based features like directional features, distance based features, geometric feature etc., mostly used separately. In this paper, Binary Area Matrix calculation is introduced. The performance of the Binary zone area matrix is measured individually and with combinations of other existing features. India is a land of multi-script country with eighteen different scripts authorized by The Government of India Sridhar (Stud Linguist Sci 30(1):149–165, 2000). Many minor languages are available in Indian with its own scripts. Such one of the language is Saurashtra language which belongs to the Indo Aryan languages. We applied our method in this language for character recognition. For each letter of Saurashtra binary zone area matrix, zone entropy matrix, zone Euler matrix and Chain for weighted matrix features of 54 identical zones of the image in 0$$^\circ $$, 90$$^\circ $$, 180$$^\circ $$, 270$$^\circ $$ are extracted. The Performance of features is examined using SVM Classifiers. Combination having a binary zone area matrix, zone entropy and zone Euler can be classified into different text types. We obtained around 99% of recognition rate.

Shape Detection and Classification in the Analysis of Images Taken from UAVs

Shape Detection and Classification in the Analysis of Images Taken from UAVs

Water use trend analysis: A non-parametric method for the environmental Kuznets curve detection

Understanding of the trend in water use with possible relation to economic development is essential for forecasting future water demand and developing response strategies. The environmental Kuznets curve hypothesis asserts that pollution emissions and natural resource use often follow an inverted-U shape. This paper develops a piecewise Mann-Kendall method to address inverted-U shape detection based on a non-parametric approach. P-values of the piecewise Mann-Kendall method statistic are identified using the exhaustion method, approximation method or analytic method, depending on the data size. Tests of the piecewise Mann-Kendall method on synthetic data indicate that the developed method provides reasonable type I error and power. The method is successfully applied to pattern detection in real water use. Water uses in a few countries and provinces in China present the environmental Kuznets curve. Unlike the traditional parametric quadratic regression method which is sensitive to data skewness, this non-parametric method offers consistent environmental Kuznets curve detection regardless of the original or logarithmic form of data being used.

Novel Integrated Helical Design of Single Optic Fiber for Shape Sensing of Flexible Robot

With the evolution of technology, it is now possible to build more flexible surgical instruments with multiple degrees of freedom that can be deployed in natural orifice translumenal endoscopic surgery, further reducing tissue damage, blood loss, and recovery time. However, the limits of flexible robots are mainly represented by the lack of accurate position feedback during the surgical procedure. The most critical problems of shape sensors are size and quantity limits, as well as sterilizability. This paper presents a novel helical configuration of single optic fiber with multiple fiber Bragg grating sensors to measure the shape of flexible robots. Detailed design of helix parameters, simulation and verification experiments were performed. We have shown the feasibility of helical configuration to reduce the effect of temperature, and detect the torsion and bending of the flexible shaft. The experimental results demonstrated the potential to provide a shape detection for flexible robot.

Automated fluorescence microscopy image analysis of Pseudomonas aeruginosa bacteria in alive and dead stadium

Fluorescent microscopy techniques take advantage of observing even single cells in live and dead stadium, and make it possible to selectively recognize specific components of biomolecular structures. This methodology is based on Green Fluorescent Protein (GFP) recognition of biochemical activities of individual microbial cells visible in screening. Unfortunately, recognition perception of human professional for fluorescent signals can be affected by various environmental factors what can lead to false interpretation of the results. Therefore intelligent computer method for fluorescent signal counting can be a great assistance at work.In this article we present experimental research results on the development of new automated fluorescence microscopy image analysis, implemented for Pseudomonas aeruginosa bacteria. Proposed method is composed of two stages of image processing. In the first, we enhance the image and extract only important bacteria shapes into simplified image. In the second, this simplification is used for detection of rod shape and spherical shape bacteria. At the end of processing statistical analysis is performed to evaluate number of bacteria in dead and alive stadium.

Visual texture agnosia in dementia with lewy bodies and Alzheimer’s disease

Abstract Background Neuroimaging and some clinical studies have reported that the ventral visual pathway is relevant for visual texture recognition. Although a variety of visual deficits have been reported in patients with Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), visual material identification and texture recognition have not been thoroughly examined. Objectives To investigate visual texture recognition in patients with AD and DLB and to clarify the relationship between visual texture recognition and various visuoperceptual functions. Methods Twenty-five patients with probable DLB, 53 patients with probable AD, and 32 age-matched healthy controls were included. We assessed visual texture recognition of real materials/images and visuoperceptual functions including contrast sensitivity, color perception, stereopsis, shape detection, and position in space. Results DLB patients showed disproportionate deficits in visuoperceptual functions and visual texture recognition compared with AD patients and controls, but these dysfunctions were not correlated with each other. AD patients had significantly impaired visual texture recognition but with intact visuoperceptual functions, except contrast sensitivity. Using an optimal cut-off score according to the receiver operating characteristic (ROC) curve analysis, the results from the visual texture recognition of images could differentiate DLB patients from controls with a sensitivity of 92% and a specificity of 97%. Conclusions We demonstrated significantly impaired visual texture recognition in patients with DLB and AD, with patients with DLB performing significantly worse than patients with AD. Additionally, visual texture recognition and visuoperceptual functions are independently disturbed in DLB.

Group Representation of Global Intrinsic Symmetries

AbstractGlobal intrinsic symmetry detection of 3D shapes has received considerable attentions in recent years. However, unlike extrinsic symmetry that can be represented compactly as a combination of an orthogonal matrix and a translation vector, representing the global intrinsic symmetry itself is still challenging. Most previous works based on point‐to‐point representations of global intrinsic symmetries can only find reflectional symmetries, and are inadequate for describing the structure of a global intrinsic symmetry group. In this paper, we propose a novel group representation of global intrinsic symmetries, which describes each global intrinsic symmetry as a linear transformation of functional space on shapes. If the eigenfunctions of the Laplace‐Beltrami operator on shapes are chosen as the basis of functional space, the group representation has a block diagonal structure. We thus prove that the group representation of each symmetry can be uniquely determined from a small number of symmetric pairs of points under certain conditions, where the number of pairs is equal to the maximum multiplicity of eigenvalues of the Laplace‐Beltrami operator. Based on solid theoretical analysis, we propose an efficient global intrinsic symmetry detection method, which is the first one able to detect all reflectional and rotational global intrinsic symmetries with a clear group structure description. Experimental results demonstrate the effectiveness of our approach.

Modified correlation method to autofocus particles in digital in-line holography

A method is proposed to automatically evaluate the focal planes of spherical particles. This method compares the correlation coefficients of multiple reconstructed planes relative to a reference plane. The particles are located where a minimum correlation is found, and reconstructions are made using an angular spectrum propagator. The Hough transform is employed to segment the hologram, thereby enabling the detection of circular shapes, such as Airy patterns, and the edges of the particles themselves. The autofocus is improved by creating a correlation matrix using an iterative process, which reduces the computational cost of the particle display processes in their respective focal planes. A theoretical model was studied to estimate the longitudinal and transverse magnifications of the focused particles caused by the influence of aberrations in the reconstruction of digital holograms due to the spherical reference wave used. Experimentally, laser light was used to illuminate 5-μm latex particles, which was recorded by a CCD camera with a 9.9-μm pixel size. The reconstructions measured an average particle radius of 71.3±16.3 μm in the average focal plane, which was estimated to be 60.65±0.22 mm from the hologram where the magnifications were considered.

Automatic extraction of blocks from 3D point clouds of fractured rock

This paper presents a new method for extracting blocks and calculating block size automatically from rock surface 3D point clouds. Block size is an important rock mass characteristic and forms the basis for several rock mass classification schemes. The proposed method consists of four steps: 1) the automatic extraction of discontinuities using an improved Ransac Shape Detection method, 2) the calculation of discontinuity intersections based on plane geometry, 3) the extraction of block candidates based on three discontinuities intersecting one another to form corners, and 4) the identification of “true” blocks using an improved Floodfill algorithm. The calculated block sizes were compared with manual measurements in two case studies, one with fabricated cardboard blocks and the other from an actual rock mass outcrop. The results demonstrate that the proposed method is accurate and overcomes the inaccuracies, safety hazards, and biases of traditional techniques.

Hybrid Clustering And Boundary Value Refinement for Tumor Segmentation using Brain MRI

The method of brain tumor segmentation is the separation of tumor area from Brain Magnetic Resonance (MR) images. There are number of methods already exist for segmentation of brain tumor efficiently. However it’s tedious task to identify the brain tumor from MR images. The segmentation process is extraction of different tumor tissues such as active, tumor, necrosis, and edema from the normal brain tissues such as gray matter (GM), white matter (WM), as well as cerebrospinal fluid (CSF). As per the survey study, most of time the brain tumors are detected easily from brain MR image using region based approach but required level of accuracy, abnormalities classification is not predictable. The segmentation of brain tumor consists of many stages. Manually segmenting the tumor from brain MR images is very time consuming hence there exist many challenges in manual segmentation. In this research paper, our main goal is to present the hybrid clustering which consists of Fuzzy C-Means Clustering (for accurate tumor detection) and level set method(for handling complex shapes) for the detection of exact shape of tumor in minimal computational time. using this approach we observe that for a certain set of images 0.9412 sec of time is taken to detect tumor which is very less in comparison to recent existing algorithm i.e. Hybrid clustering (Fuzzy C-Means and K Means clustering).

Research and Development Trend of Shape Control for Cold Rolling Strip

Shape is an important quality index of cold rolling strip. Up to now, many problems in the shape control domain have not been solved satisfactorily, and a review on the research progress in the shape control domain can help to seek new breakthrough directions. In the past 10 years, researches and applications of shape control models, shape control means, shape detection technology, and shape control system have achieved significant progress. In the aspect of shape control models, the researches in the past improve the accuracy, speed and robustness of the models. The intelligentization of shape control models should be strengthened in the future. In the aspect of the shape control means, the researches in the past focus on the roll optimization, mill type selection, process optimization, local strip shape control, edge drop control, and so on. In the future, more attention should be paid to the coordination control of both strip shape and other quality indexes, and the refinement of control objective should be strengthened. In the aspects of shape detection technology and shape control system, some new types of shape detection meters and shape control systems are developed and have successfully industrial applications. In the future, the standardization of shape detection technology and shape control system should be promoted to solve the problem of compatibility. In general, the four expected development trends of shape control for cold rolling strip in the future are intelligentization, coordination, refinement, and standardization. The proposed research provides new breakthrough directions for improving shape quality.

PROGRESSION OF VISUAL FIELDS IN POSTERIOR CORTICAL ATROPHY MIRRORS THAT OF COGNITIVE DEFICITS

The significance of visual field defects (VFD) in posterior cortical atrophy (PCA) has been questioned in face of coexisting higher-order visual disturbances. The relationship between pattern of VFDs and that of cognitive deficits may give insight into the mechanism of VFDs in PCA. Twenty-one patients with PCA had visual field tests performed using Humphrey automated perimetry at baseline and follow-up (mean duration 2.5 years; number of assessments 2–4). Mean deviation (MD) per hemifield was calculated and the ratio between MD in the right and left hemifield (R/LMDratio) established for every assessment. Cognitive measures consisted of scores created to summarise performance on tests of unilateral (Object Perception (OP); Space Perception (SP); Spelling; Arithmetic) and bilateral cognitive functions (Shape Detection (SD); Figure-Ground Discrimination (FGD)). Cognitive scores were compared with R/LMDratio at baseline using Spearman's correlation. Progression in cognitive tests was analysed according to time and contemporary R/LMDratio using mixed model linear regression. All patients had abnormal HFA at presentation, consisting of incomplete homonymous hemianopia (HH) more marked in one hemifield in all but one patient. The more affected hemifield was the left in 14 patients (66%). At baseline R/LMD did not correlate with score on OP (ρ=0.23,p<0.3), SP (ρ=0.12, p<0.6), Arithmetic (ρ =-0.24, p<0.28), or Spelling (ρ =-0.25, p<0.28). On the longitudinal analysis, increment of one unit in RLMDratio was associated with decrement of -0.78 in Spelling (p<0.01) and -0.83 in Arithmetic (p<0.02), but had no effect on OP or SP (slope 0.001, p<0.9; and 0.01, p<0.9, respectively). Increasing 1 unit on the log of RLMDratio absolute value (RLMD approached 1) was associated with decline of 0.73 (p<0.03) in FGD and 0.55 (p<0.04) in SD. Predominant right HH was associated with greater decline on cognitive functions relying on the left hemisphere, suggesting that VFDs result from extension of degeneration into the contralateral occipital lobe. This was further supported by the association between bilateral VFDs and deterioration on bilateral occipital lobe functions. Predominant left HH did not correlate with greater right hemisphere deficits, which may be explained by the occurrence of the latter in all patients, as a consequence of PCA case definition.

Liver Venous Tree Separation via Twin-Line RANSAC and Murray's Law.

It is essential for physicians to obtain the accurate venous tree from abdominal CT angiography (CTA) series in order to carry out the preoperative planning and intraoperative navigation for hepatic surgery. In this process, one of the important tasks is to separate the given liver venous mask into its hepatic and portal parts. In this paper, we present a novel method for liver venous tree separation. The proposed method first concentrates on extracting potential vessel intersection points between hepatic and portal venous systems. Then, the proposed method focuses on modeling the vessel intersection neigh-borhoods with a robust twin-line random sample consensus (RANSAC) shape detector. Finally, the proposed method conducts the venous tree separation based on the results of the twin-line RANSAC as well as physical constraints posed by Murray's Law. We test our method on 22 clinical CTA series and demonstrate its effectiveness.

Biological traits, rather than environment, shape detection curves of large vertebrates in neotropical rainforests.

Line transect surveys are widely used in Neotropical rainforests to estimate the population abundance of medium- and large-sized vertebrates. The use of indices such as encounter rate has been criticized because the probability of animal detection may fluctuate due to the heterogeneity of environmental conditions among sites. In addition, the morphological and behavioral characteristics (biological traits) of species affect their detectability. In this study, we compared the extent to which environmental conditions and species' biological traits bias abundance estimates in terra firme rainforests in French Guiana. The selected environmental conditions included both physical conditions and forest structure covariates, while the selected biological traits included the morphological and behavioral characteristics of species. We used the distance sampling method to model the detection probability as an explicit function of environmental conditions and biological traits and implemented a model selection process to determine the relative importance of each group of covariates. Biological traits contributed to the variability of animal detectability more than environmental conditions, which had only a marginal effect. Detectability was best for large animals with uniform or disruptive markings that live in groups in the canopy top. Detectability was worst for small, solitary, terrestrial animals with mottled markings. In the terra firme rainforests that represent ~80% of the Amazonia and Guianas regions, our findings support the use of relative indices such as the encounter rate to compare population abundance between sites in species-specific studies. Even though terra firme rainforests may appear similar between regions of Amazonia and the Guianas, comparability must be ensured, especially in forests disturbed by human activity. The detection probability can be used as an indicator of species' vulnerability to hunting and, thus, to the risk of local extinction. Only a few biological trait covariates are required to correctly estimate the detectability of the majority of medium- and large-sized vertebrates. Thus, a biological trait model could be useful in predicting the detection probabilities of rare, uncommon, or localized species for which few data are available to fit the detection function.

Shape Sensing Monitoring System Based on Fiber-Optic Strain Measurements: Laboratory Tests

In the context of the characterization of the shape of flying sails whilst racing, a novel method for real-time form-finding of flexural beams based on strain measurements has been developed and implemented. The very large displacements and deformations occurred on the beam pose specific demands both to the algorithm for shape detection and to the materials and sensors to use in the practical implementation, which are described and addressed in this paper. The developed method is implemented by installation of fiber Bragg grating (FBG) sensors on a beam, which are used to evaluate the curvature at specific cross-sections. The deformation curve is reconstructed by integration of local curvatures and interpolation. The effectiveness of the developed method is verified by tests on a physical model. An image-based monitoring system is further employed to validate the concept and the tests conducted with the FBG sensors. This allows the performance of an additional series of sensitivity tests in order to define the most relevant measurement parameters and characterize the accuracy of the developed method.

Tile quality detection system based on an object imaging method

Due to the disadvantages of traditional imaging methods, an imaging method based on object imaging has been proposed in this paper. This imaging method only images objects that are of interest and filters other objects. This paper mainly applies this imaging method to detect the quality of tiles by detection of special shapes. If the printing graphics of the tiles meet our requirements, a quality detection system will display the graphics needing quality detection on a monitor. Otherwise, no graphics are displayed on the monitor if the printing graphics do not meet requirements. The system includes: the use of communication between ARM and DSP under the DM6446 platform, the call to a multiple-algorithm, and design of a specific graphic imaging algorithm. The system removes the artificial testing steps in the process of quality detection, improves the speed and accuracy of quality detection and reduces the labor intensity required from inspectors. The preliminary studies show the feasibility and practicability of this system, and the preliminary experimental results show that an imaging method based on object imaging can be applied to quality detection of tiles and can solve existing problems for quality detection.

Simulation study comparing the helmet-chin PET with a cylindrical PET of the same number of detectors

There is a growing interest in developing brain PET scanners with high sensitivity and high spatial resolution for early diagnosis of neurodegenerative diseases and studies of brain functions. Sensitivity of the PET scanner can be improved by increasing the solid angle. However, conventional PET scanners are designed based on a cylindrical geometry, which may not be the most efficient design for brain imaging in terms of the balance between sensitivity and cost. We proposed a dedicated brain PET scanner based on a hemispheric shape detector and a chin detector (referred to as the helmet-chin PET), which is designed to maximize the solid angle by increasing the number of lines-of-response in the hemisphere. The parallax error, which PET scanners with a large solid angle tend to have, can be suppressed by the use of depth-of-interaction detectors. In this study, we carry out a realistic evaluation of the helmet-chin PET using Monte Carlo simulation based on the 4-layer GSO detector which consists of a 16 × 16 × 4 array of crystals with dimensions of 2.8 × 2.8 × 7.5 mm3. The purpose of this simulation is to show the gain in imaging performance of the helmet-chin PET compared with the cylindrical PET using the same number of detectors in each configuration. The sensitivity of the helmet-chin PET evaluated with a cylindrical phantom has a significant increase, especially at the top of the (field-of-view) FOV. The peak-NECR of the helmet-chin PET is 1.4 times higher compared to the cylindrical PET. The helmet-chin PET provides relatively low noise images throughout the FOV compared to the cylindrical PET which exhibits enhanced noise at the peripheral regions. The results show the helmet-chin PET can significantly improve the sensitivity and reduce the noise in the reconstructed images.

Target Type Modulates the Effect of Task Demand on Reflexive Focal Attention.

Focusing attention on a limited space within the environment allows us to concentrate our resources selectively on that location while ignoring the rest of the space. In this study we investigated how the deployment of the focal attention in foveal vision can be affected by task and stimuli specificity. In particular, we measured the cue-size effect in four experiments: shape detection (Experiment 1), shape discrimination (Experiment 2), letter detection (Experiment 3), and letter discrimination (Experiment 4). Our results highlight that, although the focal component can be elicited by different tasks (i.e., detection or discrimination) and by using different types of stimuli (i.e., shapes or letters), those effects interact with each other. Specifically, the effect of focal attention is more noticeable when letter stimuli are used in the case of a detection task, while no difference between letters and geometrical shapes is observed in the discrimination task. Furthermore, the analysis of the cue-size effect across the four experiments confirmed that the deployment of focal attention in foveal vision is mainly reflexive.

A New Algorithm for Shape Detection

A New Algorithm for Shape Detection