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Visual contour tracking based on inner-contour model particle filter under complex background

Visual contour tracking based on inner-contour model particle filter under complex background

This paper has presented a method of visual contour track- ing based on particle filter for inner-contour model under complex background. This novel method fused the gradient feature, local color feature, and global color feature naturally to achieve robust contour tracking in cluttered environment. Specifically, the proposed algorithm first used Sobel edge de- tector to detect the edge information along the normal lines of the contour, and then sampled the inner part of the nor- mal lines to get the local color information, which was com- bined with the edge information to construct new normal line likelihood. After that, all the inner color information was used to construct global color likelihood. Finally, the edge in- formation, local color information and global color informa- tion are fused together as new observation likelihood. The experimental results demonstrated that, compared with gradient-only feature method, the proposed algorithm was effective and robust in dealing with cluttered background, and it was also computationally efficient and could run com- pletely in real time.

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Robust Facial Features Localization on Rotation Arbitrary Multi-View Face in Complex Background

Robust Facial Features Localization on Rotation Arbitrary Multi-View Face in Complex Background

Abstract — Focused on facial features localization on multi-view face arbitrarily rotated in plane, a novel detection algorithm based improved SVM is proposed. First, the face is located by the rotation invariant multi-view (RIMV) face detector and its pose in plane is corrected by rotation. After the searching ranges of the facial features are determined, the crossing detection method which uses the brow-eye and nose-mouth features and the improved SVM detectors trained by large scale multi-view facial features examples is adopted to find the candidate eye, nose and mouth regions,. Based on the fact that the window region with higher value in the SVM discriminant function is relatively closer to the object, and the same object tends to be repeatedly detected by near windows, the candidate eyes, nose and mouth regions are filtered and merged to refine their location on the multi-view face. Experiments show that the algorithm has very good accuracy and robustness to the facial features localization with expression and arbitrary face pose in complex background.

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Design of Face Detection in Colour Images with Complex Background

Design of Face Detection in Colour Images with Complex Background

Next, the possible edges are found in the image to aid the decision of finding out whether if any related regions remain disconnected in the image. Thus if any face region has got segmented due to algorithm the faces can then be combined resulting in a complete face. Thus faces have been detected. This algorithm works well not only for single face images but also for images with multiple faces. Its robustness can be measured from the fact that it also works very well for complex backgrounds as it does for simple backgrounds. The various advantages and disadvantages have been mentioned in the next section.

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Effective Detection of Moving Objects Using Complex Background Subtraction

Effective Detection of Moving Objects Using Complex Background Subtraction

The output of the change detection module is the binary image that contains only two labels, i.e., „0‟ and „255‟, representing as „background‟ and „foreground‟ pixels respectively, with some noise. The goal of the connected component analysis is to detect the large sized connected foreground region or object. This is one of the important operations in motion recognition [9]. The pixels that are cooperatively associated can be clustered into changing or moving objects by analyzing their connectivity. In binary image analysis, the object is extracted using the connected component cataloging procedure, which consist of transmission distinctive label to each maximally connected foreground province of pixels. One of the imperative classification [7] approaches is “classical sequential labeling algorithm”. It is based on two raster scan of binary image. The original scan performs the provisional labeling to each foreground region pixels by checking their connectivity of the scanned image. When a foreground pixel with two or more than two foreground neighboring pixels carrying the same label is found, the labels associated with those pixels are registered as being equivalent. That means these regions are from the same object. The handling of equivalent labels and merging thereafter is the most complex task. The first scan gives temporary labels to the foreground pixels according to their connectivity. The connectivity check can be done with the help of either a 4-connectivity or 8-connectivity approach. 8- connectivity approach is used. Here, the idea is to label the whole blob at a time to avoid the label redundancies. The labeling operation scans the image moving along the row until it comes to the point P, for which S = {255}.

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Complex Background Image Detection and Processing Based on Machine Vision

Complex Background Image Detection and Processing Based on Machine Vision

This paper suggests a new method that generates sampling point along the guide line for linear contour defect detection and recognition. The method registers the vector data with the measured image to generate sampling points that can cover the contour accurately. Next, these sampling points are saved into a test file for quick batch detection of the same products. Then pictures are taken to eliminate the complex background noise on the objects to carry out a series of image pretreatment. On this basis, the algorithm that using SUSAN Operator is used to determine the location of the sampling points. Also, the potential defects are identified and classified. The method has good adaptability to the detection of linear image contour. It is of high application value due to reliability and real-time capability.

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Signal Contamination Model for Adaptive Detection Performance of Local Anomalies in Hyper-spectral Images

Signal Contamination Model for Adaptive Detection Performance of Local Anomalies in Hyper-spectral Images

www.ijaera.org 51 Existing background suppression methods for single-frame infrared image are mainly classified into the following two categories. One is the filtering methods and the other one is statistical regression. The filtering methods include processing in space domain, which uses filter templates, morphological operators, etc., and processing in frequency domain, which relies on eliminating the low-frequency component. The filtering methods can suppress most part of the correlative background but may be easily interfered because of strong fluctuation of complex background clutters. Regression methods are classified as parametric and nonparametric methods. Classical parametric regression methods rely on a specific model of background clutters and seek to estimate the parameters of this assumed model [2, 3-6]. In comparison with the parametric methods, nonparametric methods rely on the data itself to estimate the regression function. In practice, nonparametric methods are more suitable and adaptive for complex background because of lack of a priori knowledge about background clutters. As a result of the recent development of machine learning theory, kernel methods have been used widely in pattern analysis and statistical regression problems [4 7]. In this letter, a small-target detection algorithm in infrared image is proposed, which predicts and eliminates the complex background clutter by a kernel-based nonparametric regression model and obtains residual “pure” target-like image which only consists of noise and possible targets on local regions in infrared images. Then, a two-parameter constant false alarm rate (CFAR) detecting algorithm is performed to extract the small target from the “pure” target-like image [8-11].

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Distribution of Anopheles in Vietnam, with particular attention to malaria vectors of the Anopheles minimus complex

Distribution of Anopheles in Vietnam, with particular attention to malaria vectors of the Anopheles minimus complex

Based on cattle collections, An. minimus s.l. and An. sinen- sis were the main species in northern Vietnam, whereas An. aconitus and An. vagus were dominant in central Viet- nam. Anopheles minimus and An. harrisoni of the Minimus complex are present over the northern, central and south- eastern Vietnam, down to latitude 11°N. Malaria trans- mission is still high in central Vietnam and along border- ing countries. Future entomological surveys in the surrounding countries and, on a larger scale throughout southeast Asia, are required to molecularly identify the different members of the Minimus and Aconitus Sub- groups to clarify the precise distributions of each member and to improve vector control strategies.

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Narrowing the gap between eye care needs and service provision: a model to dynamically regulate the flow of personnel through a multiple entry and exit training programme

Narrowing the gap between eye care needs and service provision: a model to dynamically regulate the flow of personnel through a multiple entry and exit training programme

Simulation of a model is an effective and efficient tool that should be used with all human resource models. To show its application, a computable model has been pre- sented to describe the flow of personnel though a multi- ple-entry, multiple-exit training scheme and thence into the health workforce. The model presented allows a plan- ner to integrate accessible yet complex interactions by simulating and compensating for the effects over time of a range of differing scenarios. By understanding complex- ity and the environment within which the model will operate, intended and unintended consequences can be observed and adjusted.

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A SURVEY ON COMPARISION AND PERFORMANCE ANALYSIS OF TEXT EXTRACTION TECHNIQUES

A SURVEY ON COMPARISION AND PERFORMANCE ANALYSIS OF TEXT EXTRACTION TECHNIQUES

Various methods have been proposed in the past for detection and localization of text in images and videos. These approaches take into consideration different properties related to text in an image such as color, intensity, connected-components, edges etc. These properties are used to distinguish text regions from their background and/or other regions within the image. The algorithm proposed by Wang and Kangas in [5] is based on color clustering. The input image is first pre-processed to remove any noise if present. Then the image is grouped into different color layers and a gray component. This approach utilizes the fact that usually the color data in text characters is different from the color data in the background. The potential text regions are localized using connected component based heuristics from these layers. Also an aligning and merging analysis (AMA) method is used in which each row and column value is analyzed [5]. The experiments conducted show that the algorithm is robust in locating mostly Chinese and English characters in images; some false alarms occurred due to uneven lighting or reflection conditions in the test images.

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A Wavelet Neural Networks License Recognition Algorithm and Its Application

A Wavelet Neural Networks License Recognition Algorithm and Its Application

In this paper, a novel algorithm based on adaptive wavelet neural network is presented for license character recognition. The detailed working process is expressed as follows: first to transform the color vehicle image into index image, then the index image will undergo wavelet transform to obtain high frequency sub-bands (LH, HL, HH). Secondly, features of the wavelet coefficients such as the mean, energy, entropy can be worked out, and a dynamic threshold will be obtained through these features. Thirdly, license candidates and non-license candidates were obtained by applying morphological operations. Fourthly, the extracted index license image will also undergo a wavelet transform to obtain high frequency sub-bands. And the bigger wavelet coefficients will be reserved through the threshold and undergo normalize process. Fifthly, the useful wavelet coefficients of each sub-bands will be projected horizontally and vertically to extract a group of statistical feature of license character. At last, with the input of character feature vector, the wavelet neural network will recognize it correctly. The experimental results with various kinds of the vehicle images demonstrate that the proposed method is effective to recognize license character automatically in a vehicle image. It is robust for license size, license color, background complexity and various illuminations.

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Implementation of a successful eradication protocol for Burkholderia Cepacia complex in cystic fibrosis patients

Implementation of a successful eradication protocol for Burkholderia Cepacia complex in cystic fibrosis patients

Though less prevalent than P. aeruginosa, CF patients may acquire other respiratory pathogens including spe- cies of the Burkholderia cepacia complex (Bcc) [9]. Bcc represents a group of genetically related bacteria associ- ated with a heterogeneous clinical course ranging from asymptomatic colonization to fulminant respiratory fail- ure [10, 11]. Chronic colonization with Bcc is associated with antibiotic resistance, increased risk of respiratory failure, and worsened mortality [10, 12]. Although Bcc eradication has been previously described, implementa- tion of a protocolized approach toward Bcc eradication has not been fully studied [13, 14].

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A biologically inspired neural network controller for ballistic arm movements

A biologically inspired neural network controller for ballistic arm movements

Human beings are able to accomplish extremely complex motor tasks in all kinds of environments by means of a highly organized architecture including sensors, process- ing units and actuators. From a cognitive and develop- mental perspective, and a rehabilitation standpoint, it is necessary to fully understand the complex interactions between the controller (the Central Nervous System) and the controlled object (all parts of the body)[1]. These interactions describe the process of motor control for which many theories have been developed. As far as the generation of motor commands is concerned, in literature it is generally acknowledged that nervous system gener- ates motor commands based on internal models able to take account of the kinematics and the dynamics of the biomechanical structures [2-4]. These models can be described as groups of neural connections that intrinsi- cally contain information about biomechanical proper- ties of the human body in relation both to the environment and the subject's experience.

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Artificial Life as an Aid to Astrobiology: Testing Life Seeking Techniques

Artificial Life as an Aid to Astrobiology: Testing Life Seeking Techniques

Scouting experiments were run on these snapshots to sample 800 locations in the simulation space. Figure 3 shows the probed locations in the left column. Their density indicates areas of high interest to the scouting algorithm. We used hierarchical clustering with subsequent expectation maximization (performed with mclust in R [22, 23]) to automatically identify clusters in the sampling positions. The number of clusters identified during expectation maximization can be seen in the middle column as peaks of the Bayesian information criterion. We used the samples allocated to a cluster (shown in Fig. 3 only for the case of three biota patches: panel J) and calculated their mean position as prediction for the location of biota in the simulation space. These predicted positions are marked with + in panels C, F and I. If the scouting is repeated with an alternate seed value for its random generator, the evolution of the sampling positions will take a different course; predictions from four additional runs are marked with for comparison. The localization is fairly good, despite the complex chemical background (panel D, for example, shows the scouting of Fig. 2B).

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An Improved Randomized Circle Detection Algorithm Using in Printed Circuit Board Locating Mark

An Improved Randomized Circle Detection Algorithm Using in Printed Circuit Board Locating Mark

In place of creating an accumulator array for mapping the extracted edge pix- els in images to the circle parameters in HT-based method, Randomized Circle Detection (RCD) [6] does not use an accumulator for saving the information of related parameters in Randomized Sample Consensus (RANSAC) [7] based me- thod. The main concept is that the algorithm randomly chooses four edge pixels from the image first, and then uses a distance criterion to determine whether they belong to a possible circle in the image. After finding a possible circle, RCD uses an evidence-collecting step to further determine whether the candidate cir- cle is a real-circle. Since RCD does not need extra accumulator storage, the mem- ory requirements needed in RCD are only a few variables, and the method has some other advantages such as real-time speed and more robust to noise. How- ever, sampling for RCD randomly happens on all edge pixels of the whole image and verification of the hypothetical circles also use all the edge pixels, which both occupy a mass of time and obtain uncertainty of results [8]. To solve these prob- lems, an improved randomized circle detection algorithm in the complex back- ground image is proposed in the paper, which uses improved RCD algorithm and the characteristic of circularity. Firstly, the improved RCD based on connected contours is applied to detect possible circles. Then, the characteristic of circularity is used to discard some inaccurate possible circles. The algorithm is faster than RCD for it samples only on the connected curve [8]. The experimental results show that the refined algorithm has good detection performance.

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SCCmecFinder, a Web-Based Tool for Typing of Staphylococcal Cassette Chromosome mec in Staphylococcus aureus Using Whole-Genome Sequence Data

SCCmecFinder, a Web-Based Tool for Typing of Staphylococcal Cassette Chromosome mec in Staphylococcus aureus Using Whole-Genome Sequence Data

ABSTRACT Typing of methicillin-resistant Staphylococcus aureus (MRSA) is impor- tant in infection control and surveillance. The current nomenclature of MRSA in- cludes the genetic background of the S. aureus strain determined by multilocus se- quence typing (MLST) or equivalent methods like spa typing and typing of the mobile genetic element staphylococcal cassette chromosome mec (SCCmec), which carries the mecA or mecC gene. Whereas MLST and spa typing are relatively simple, typing of SCCmec is less trivial because of its heterogeneity. Whole-genome se- quencing (WGS) provides the essential data for typing of the genetic background and SCCmec, but so far, no bioinformatic tools for SCCmec typing have been avail- able. Here, we report the development and evaluation of SCCmecFinder for charac- terization of the SCCmec element from S. aureus WGS data. SCCmecFinder is able to identify all SCCmec element types, designated I to XIII, with subtyping of SCCmec types IV (2B) and V (5C2). SCCmec elements are characterized by two different gene prediction approaches to achieve correct annotation, a Basic Local Alignment Search Tool (BLAST)-based approach and a k-mer-based approach. Evaluation of SCC- mecFinder by using a diverse collection of clinical isolates (n ⫽ 93) showed a high typeability level of 96.7%, which increased to 98.9% upon modification of the de- fault settings. In conclusion, SCCmecFinder can be an alternative to more laborious SCCmec typing methods and is freely available at https://cge.cbs.dtu.dk/services/ SCCmecFinder.

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Tibial nerve stimulation with a miniature, wireless stimulator in chronic peripheral neuropathic pain

Tibial nerve stimulation with a miniature, wireless stimulator in chronic peripheral neuropathic pain

Abstract: Peripheral neuropathic pain (PNP) and complex regional pain syndrome (CRPS) can be effectively treated with peripheral nerve stimulation. In this clinical trial report, effec- tiveness of novel, miniature, wirelessly controlled microstimulator of tibial nerve in PNP and CRPS was evaluated. In this pilot study the average preoperative visual analog scale (VAS) score in six patients was 7.5, with 1, 3 and 6 months: 2.6 (p=0.03), 1.6 (p=0.03), and 1.3 (p=0.02), respectively. The mean average score in the six patients a week preceding the baseline visit was 7.96, preceding the 1, 3 and 6 month visits: 3.32 (p=0.043), 3.65 (p=0.045), and 2.49 (p=0.002), respectively. The average short-form McGill pain score before surgery was 23.8, and after 1, 3 and 6 months it was 11.0 (p=0.45), 6.3 (p=0.043), and 4.5 (p=0.01), respectively. Applied therapy caused a reduction of pain immediately after its application and clinical improvement was sustained on a similar level in all patients for six months. No complications of the treatment were observed. Intermittent tibial nerve stimulation by using a novel, miniature, wirelessly con- trolled device can be effective and feasible in PNP and CRPS. It is a safe, minimally invasive, and convenient neuromodulative method.

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First report of cavitary pneumonia due to community acquired Acinetobacter pittii, study of virulence and overview of pathogenesis and treatment

First report of cavitary pneumonia due to community acquired Acinetobacter pittii, study of virulence and overview of pathogenesis and treatment

elegans killing assays and the BioFilm Ring Test® showed very low virulence potential and a poor ability to form biofilm as recently observed [11, 12]. The significant variability of virulence described among A. baumannii complex species probably explains the sub-acute clinical course unlike the fulminant evolution usually associated with Acinetobacter community-acquired pneumonia in tropical areas [12 – 14]. Moreover, the mortality rate for patients infected with A. pittii seems to be lower than for A. baumannii (15% versus 40%) [4, 10]. Finally, the hosts ’ immune status and tobacco consumption seem to play a crucial role to facilitate infection. A. pittii and A. baumannii appear genetically and metabolically similar [15] and probably share the same risk factors for causing community-acquired infections: smoking, excessive alco- hol consumption, diabetes mellitus and chronic lung dis- ease [13, 14]. In this case, the patient is diabetic, smokes and also has lupus, a condition known to increase the risk of infection with or without immunosuppressive drugs [16]. A. pittii is widely distributed in the environ- ment and may contaminate food and animals, thus humans could acquire skin and/or oral carriage which subsequently favours infection [13, 17]. A study with more patients would allow us to better characterize the virulence of A. pittii and the host-pathogenic interaction but seems difficult due to the low prevalence of this type of infection.

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Morphological assessment of the stylohyoid complex variations with cone beam computed tomography in a Turkish population

Morphological assessment of the stylohyoid complex variations with cone beam computed tomography in a Turkish population

form shape, elongated type and nodular calcification pattern have the highest mean age values between the morphological groups, respectively. There was a compelling difference between gender and cited mor- phological variations. According to their shape varia- tions, linear and scalariform types were more frequent in males, while moniliform and pseudoduplicated types were observed mostly in females. Elongated SHC type was significantly high in males, whereas Table 4. Patient distribution and length, thickness, sagittal and transverse angle values of stylohyoid complex (SHC) among the age groups

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Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE

Impact of Earnings per Share on Market Price of Share with Special Reference to Selected Companies Listed on NSE

The proposed dual-microphone algorithm utilizes the coherence function between the input signals and yields a filter, whose coefficients are computed, based on the real and imaginary parts of the coherence function. The proposed algorithm makes no assumptions about the placement of the noise sources and addresses the problem in its general form .In this contribution a system was proposed which exploits the short-term spectral energy distributions to detect and reduce wind noise in noisy speech signal. Based on the complex coherence to estimate the wind noise PSD in a dual microphone signal is presented. An evaluation with wind noise recordings shows that the proposed method outperforms the state-of-the-art complex coherence a approach for background noise estimation and leads to similar results as other approaches especially designed for wind noise reduction with a significantly lower computational complexity.

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Exome sequencing reveals a novel TTC19 mutation in an autosomal recessive spinocerebellar ataxia patient

Exome sequencing reveals a novel TTC19 mutation in an autosomal recessive spinocerebellar ataxia patient

Neurodegeneration caused by mutations of TTC19 are classified as mitochondrial complex III deficiencies (MC3DNs), including MC3DN1 [MIM:124000] [4], which is associated with compound heterozygous or homozygous mutations of the BCS1L gene. Clinical symptoms of MC3DN are varied, but in reports on mutations of TTC19, many cases exhibit neurological disorders in adulthood, and some cases present both hemiplegia and cerebellar ataxia. Pyramidal signs were not observed in our case, but intellectual dysfunction was ob- served. As shown in previous reports, TTC19 p.Q173Rfs*4, p.L219* [1] and p.A200Afs*8 [2] are located between the first and the second TPR domains, but p.Q277*, the novel substitution we identified is located between the second and third domains, accordingly deleting half of the TPR domains. Notably, all these mutations are nonsense mutations. Clinical symptoms were mild compared with the symptoms from previously reported cases, but determining whether mutations are associated with clinical symptoms may require a longer observation of our patient’s clinical course and the accumulation of more cases.

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