Matching Success Rate Research Articles

A Method for Identification and Matching of the Picking Point for Mature Litchi under Structural Environment

A method to identify the picking point of the whole mature litchi fruit and its matching method based on binocular stereo vision under the structural environment is proposed in this paper. The mature litchi clusters in the extracted image were segmented by using the improved K-means clustering algorithm. The region of interest (ROI) of the Litchi stems is set based on the characteristics of the center of the litchi fruit region and the minimum circumscribed rectangle. Corner extraction from the main fruit bearing branch of litchi was carried out by Harris algorithm. The customized function of circle distance is used to determine the optimal corner, and then cumulative probability Hough linear detection of the Litchi stems is used to determine the straight line of the picking point. Finally, the two-dimensional pixel coordinates of the picking point are determined. Then the three-dimensional coordinates of litchi picking points are obtained by SGBM stereo matching algorithm. The experimental results show that the matching success rate of picking points can reach 86.63%. It provides the foundation for litchi harvesting robot to pick litchi fruit successful.

A Robust Solution of Integrated SITAN with TERCOM Algorithm: Weight-Reducing Iteration Technique for Underwater Vehicles' Gravity-Aided Inertial Navigation System

The robustness of the Sandia Inertial Terrain-Aided Navigation (SITAN) algorithm has a pivotal influence on underwater vehicles' Gravity-Aided Inertial Navigation Systems (GAINS). An abrupt glitch of the accuracy of the GAINS will evolve into a disaster when vehicles pass through areas of smooth gravity. In order to resolve vulnerability issues of initial error and linearization error, we propose the Correlation SITAN algorithm with Weight-Reducing Iteration Technique (CSITAN + WRIT), in which the correlation process equals Terrain Contour Matching (TERCOM). The CSITAN algorithm is a Multipoint-based Extended Kalman Filtering (MEKF) method, which can work in real time. First, we need to derive the state equation and observation equation of the Multipoint-based SITAN algorithm based on the principle of the traditional SITAN algorithm. Then the accuracy of the state prediction can be improved, and the linearization error can be reduced by the correlation method based on TERCOM. Finally, the WRIT is utilized to reduce the possible influence of gross errors existing in the results of the MEKF and to extract a value with higher precision. The experimental results show that CSITAN + WRIT can achieve better accuracy and higher success rate of matching and can improve the possibilities of the occurrence of large matching errors than traditional SITAN methods in areas with smooth gravity. Copyright © 2017 Institute of Navigation

Text Authorship Identified Using the Dynamics of Word Co-Occurrence Networks.

Automatic identification of authorship in disputed documents has benefited from complex network theory as this approach does not require human expertise or detailed semantic knowledge. Networks modeling entire books can be used to discriminate texts from different sources and understand network growth mechanisms, but only a few studies have probed the suitability of networks in modeling small chunks of text to grasp stylistic features. In this study, we introduce a methodology based on the dynamics of word co-occurrence networks representing written texts to classify a corpus of 80 texts by 8 authors. The texts were divided into sections with equal number of linguistic tokens, from which time series were created for 12 topological metrics. Since 73% of all series were stationary (ARIMA(p, 0, q)) and the remaining were integrable of first order (ARIMA(p, 1, q)), probability distributions could be obtained for the global network metrics. The metrics exhibit bell-shaped non-Gaussian distributions, and therefore distribution moments were used as learning attributes. With an optimized supervised learning procedure based on a nonlinear transformation performed by Isomap, 71 out of 80 texts were correctly classified using the K-nearest neighbors algorithm, i.e. a remarkable 88.75% author matching success rate was achieved. Hence, purely dynamic fluctuations in network metrics can characterize authorship, thus paving the way for a robust description of large texts in terms of small evolving networks.

Improved Multiple Matching Method for Observing Glacier Motion with Repeat Image Feature Tracking.

Repeat Image Feature Tracking (RIFT) is commonly used to measure glacier surface motion from pairs of images, most often utilizing normalized cross correlation (NCC). The Multiple-Image Multiple-Chip (MIMC) algorithm successfully employed redundant matching (i.e. repeating the matching process over each area using varying combinations of settings) to increase the matching success rate. Due to the large number of repeat calculations, however, the original MIMC algorithm was slow and still prone to failure in areas of high shearing flow. Here we present several major updates to the MIMC algorithm that increase both speed and matching success rate. First, we include additional redundant measurements by swapping the image order and matching direction; a process we term Quadramatching. Second, we utilize a priori ice velocity information to confine the NCC search space through a system we term dynamic linear constraint (DLC), which substantially reduces the computation time and increases the rate of successful matches. Additionally, we develop a novel post-processing algorithm, pseudosmoothing, to determine the most probable displacement. Our tests reveal the complimentary and multiplicative nature of these upgrades in their improvement in overall MIMC performance.

Extraction of digital elevation model using stereo matching with slope-adaptive patch transformation

Traditional automated DEM generation from high-resolution satellite imagery relies on area-based correlation matching methods. However, these methods often fail, especially where the slope of the terrain is very high; this results in large geometric difference in the stereo pair. To address this issue, we introduced an adaptive stereo matching scheme that incorporates image transformation for the slope in the epipolar image space. The matching patch is designed to adaptively transform the target image according to the terrain slope determined in the lower scale of the image pyramid. This transformation reduces the geometric difference between the stereoscopic images due to the image acquisition angle and the terrain slope. Experimental results with Kompsat-2 images showed that the proposed method increased the overall matching success rate by 5% and the vertical accuracy of the generated DEM improved by about 2 meters (17%).

Eye-in-hand vision-based robotic bin-picking with active laser projection

In this paper, an eye-in-hand vision-based robotic bin-picking system is proposed. The system can identify the pose of a plumbing part from a pile and grip it correctly. A monocular eye-in-hand camera and a laser projector are employed to reconstruct the 3-D point cloud of plumbing parts stacked together. The projection direction of the laser line projector is controlled to change in order to scan the pile of objects while the camera is observing. 3-D points can then be determined by the a priori known geometry between the camera and the laser line projector. To estimate the pose of an object, the iterative closest point (ICP) is employed to match the point clouds of the object and the model. The transformation between the object and the model can thus be determined. A computed closer point (CCP) approach is proposed to estimate the pose of an object since the deviation from the object to the model is initially large in nature. The proposed CCP approach combining with the ICP algorithm can improve the success rate and accuracy of point cloud matching. The proposed system has been validated by experiments with potential applications in production lines.

Automated Generation of a Digital Elevation Model Over Steep Terrain in Antarctica From High-Resolution Satellite Imagery

The automated generation of a digital elevation model over the Antarctic using stereo matching high-resolution satellite images is a challenging task. Moreover, the homogeneous radiometry in the icy environment and the strong geometric dissimilarity between stereo pairs over the steep terrain limit the use of area-based matching techniques. To overcome this issue, we propose template matching with image transformation in order to reduce the geometric dissimilarity. First, we generated epipolar resampled images to ensure the ease of estimation and handling of image dissimilarities from various viewing directions. We then utilized the normalized cross-correlation (NCC) and transformed the image patches within the matching window along the sample, line, and diagonal directions in order to improve the match rates within the steep areas. Furthermore, we tested the proposed method using Antarctic IKONOS stereo images and found that the overall matching success rate improved from 93.5% to 97.0% for all image pixels. We then computed the success rates over an area in which the NCC produced a low elevation point density and observed a more significant improvement from 58.7% to 79.26%. When compared to the manually generated elevation, the maximum vertical difference improved from 11.4 to 4.7 m. With these improvements, we can build a 1-m resolution elevation model over the glaciated high relief terrain.

Decentralized matching and social segregation

Social segregation is a ubiquitous feature of human life. People segregate along the lines of income, religion, ethnicity, language, and other characteristics. This study provides the first experimental examination of decentralized matching with search frictions and institutionalized segregation. The findings indicate that, without a segregation institution, high types over-segregate relative to the equilibrium prediction. We observe segregation attempts even when equilibrium suggests that everyone should accept everyone else. In the presence of a segregation institution, we find that, while the symmetric segregation institution increases matching success rate and efficiency in one environment, it has weak or no effect in a steep-incentive environment. By adding an entry cost to a flat-incentive market, however, the asymmetric segregation institution leads to an increased matching success rate and efficiency in both environments, which underscores the importance of a coordination device.

The OPTN Kidney Paired Donation Pilot Program (KPDPP): Reaching the Tipping Point in 2013.

Background: U.S. living donor transplants (txs) reported as paired donations increased from 34 in 2004 to 527 in 2012. The OPTN KPDPP was launched in 2010 after KPD was determined not to violate the “valuable consideration” clause in NOTA. The program continues to make important policy and online system enhancements to increase transplant opportunities for patients with willing but incompatible living donors. This report highlights progress made by the OPTN KPDPP in participation, match offers, and txs. Methods: We analyzed tx candidate (TC) and living donor (LD) data submitted from Oct 2010 - Nov 2013 by tx centers participating in the OPTN KPDPP. 2-way, 3-way and chain exchanges were found using algorithms developed by Carnegie Mellon and Johns Hopkins Universities. Match success rates were defined as the percentage of matches (one TC and his matched donor) that were accepted and led to a transplant. Results: Through Nov 2013, 133 (58%) of 231 LD tx programs have agreed to participate with 92 (40%) having entered at least 1 pair. Over 900 TCs and LDs have been entered, with over 220 eligible pairs consistently participating in each weekly match run. In 2013, on average 82 matches were found each quarter with 5% of TCs finding a match in each run. Txs increased by 420% from 10 in 2012 to 52 in 2013, even as 64% of TCs entered were highly sensitized (HS), with CPRA≥80%. Txs included 23 HS TCs. Ethnic minorities comprised 34% of txs.Figure: No Caption available.The dramatic rise in transplants can be attributed to an increased number of matches being found coupled with a rise in the match success rate from 3% in 2012 to 10% in 2013. Conclusion: With the majority of the U.S. LD tx programs now participating, the OPTN KPDPP appears to have reached a tipping point in 2013, producing increasingly more txs, including for difficult-to-match and minority TCs. Though the match success rate has risen, the OPTN KPD Work Group continues to work on ways to increase the rate beyond the current 10%. The OPTN KPDPP is a robust, increasingly successful KPD program available to all LKD programs.

Creating an infrastructure for comparative effectiveness research in emergency medical services.

Emergency medical services (EMS) providers deliver the initial care for millions of people in the United States each year. The Institute of Medicine noted a deficit in research necessary to improve prehospital care, created by the existence of data silos, absence of long-term outcomes, and limited stakeholder engagement in research. This article describes a regional effort to create a high-performing infrastructure in southwestern Pennsylvania addressing these fundamental barriers. Regional EMS records from 33 agencies in January 2011 were linked to hospital-based electronic health records (EHRs) in a single nine-hospital system, with manual review of matches for accuracy. The use of community stakeholder engagement was included to guide scientific inquiry, as well as 2-year follow up for patient-centered outcomes. Local EMS medicine stakeholders emphasized the limits of single-agency EMS research and suggested that studies focus on improving cross-cutting, long-term outcomes. Guided by this input, more than 95% of EMS records (2,675 of 2,800) were linked to hospital-based EHRs. More than 80% of records were linked to 2-year mortality, with more deaths among EMS patients with prehospital hypotension (30.5%) or respiratory distress (19.5%) than chest pain (5.4%) or nonspecific complaints (9.4%). A prehospital comparative effectiveness research infrastructure composed of patient-level EMS data, EHRs at multiple hospitals, long-term outcomes, and community stakeholder perspectives is feasible and may be scalable to larger regions and networks. The lessons learned and barriers identified offer a roadmap to answering community and policy-relevant research questions in prehospital care.

Generation and Quality Assessment of Stereo-Extracted DSM From GeoEye-1 and WorldView-2 Imagery

Digital surface models (DSMs) extracted from 15 different stereo pairs attained by the combination of GeoEye-1 (GE1) and WorldView-2 (WV2) panchromatic very high resolution (VHR) satellite images are tested. Two of them are pure same-date along-track stereo pairs, one from each VHR satellite, whereas the rest are mixed multidate across-track ones. A quality assessment on the DSMs extracted from the aforementioned stereo pairs, involving both accuracy and completeness, is carried out. Several factors are tested such as sensor model used in the bundle adjustment, number of ground control points (GCPs), radiometric characteristics, satellite imaging geometry, time between acquisition dates, and target land cover. A highly accurate light detection and ranging elevation data is used as ground truth. Overall, 3-D rational functions refined by a zero-order polynomial adjustment by using 7 or 12 GCPs performed slightly better regarding both DSM vertical accuracy and completeness. In relation to the pure stereo pairs, the DSM extracted from the GE1 stereo pair attained better vertical accuracy over the whole study area (90th percentile linear error, LE90, of 2.04 m) but lower completeness (74.50%) than the WV2 one (2.56 m and 83.35%, respectively). The undergoing hypothesis is that the blurrier images from WV2 could have influenced in the improvement of the matching success rate while reducing the vertical accuracy of extracted points. When all the 15 stereo pairs are considered, the vertical accuracy mainly depends on the convergence angle. In addition, the temporal difference between acquisition dates turned out to be the most influential factor regarding completeness values.

Accuracy of Preoperative MRI in Predicting Pathology Stage in Rectal Cancers

Few studies that meticulously match individual lymph nodes seen on MRI with their precise histologic counterparts after total mesorectal excision have been reported. The objective of this study was to determine whether preoperative MRI could detect lymph node metastases accurately in the node-by-node analysis. This was a prospective, observational cohort study. The study was conducted at a tertiary-care hospital. Forty patients with rectal cancer were enrolled. Specimens were assessed using MRI for clinical staging. After surgical resection of the tumor, the specimens were again imaged with ex vivo ultrasound scan to localize the perirectal node. The locations of each lymph node were precisely matched with its corresponding magnetic resonance image to enable a node-for-node comparison of magnetic resonance images and histologic findings. Agreement between MRI and histologic assessment of T stage was 82.5%. Of the 341 nodes harvested, 120 were too small (<3 mm) to be depicted on magnetic resonance images, and 18 of these contained metastasis (15%). A correlation between the results of MRI and histopathology was feasible for 205 lymph nodes, and the overall success rate of matching between the 2 techniques was 91.1% (205 of 221). Preoperative MRI revealed a node-by-node sensitivity and positive predictive value of 58.0%, and 61.7%. There was no difference in the diagnostic accuracy between the primary surgery subgroup and preoperative radiation subgroups. The study is limited by its heterogeneity of cohorts including the subgroup with preoperative chemoradiation and the lack of preoperative ultrasound assessment. Preoperative MRI was moderately accurate for the prediction of mesorectal lymph node metastasis. Moreover, preoperative MRI was insufficient for detecting small lymph nodes (<3 mm) with metastasis.

Linking Survey Data with Administrative Social Security Data - the Project 'Interactions Between Capabilities in Work and Private Life'

We perform a record linkage of survey data from the project “Interactions Between Capabilities in Work and Private Life: A Study of Employees in Different Work Organizations”, a sub-project of the research group “From Heterogeneities to Inequalities” at Bielefeld University, with administrative social security data from the Institute for Employment Research (IAB) at the German Federal Employment Agency. We describe both data sets with regard to the identifiers available for the record linkage (such as names and addresses), as well as the methods and procedures that were used for this record linkage. As a final result, about 73% of the survey records could be linked, which is slightly below our average matching success rate for individual data.

Local enhancement method and its applications to UAV image matching

The quality of UAV image is closely related to light,imaging angle and the feature of the ground object. There are some shortcomings in many images,such as poor visual contrast,large distortion and insufficient resolution,which cause many difficulties in subsequent image matching and orthorectification. To obtain better results in UAV image matching,the authors first calculated the degree of dispersion between gray value of pixel and image gray average to divide the image into different areas according to the discrete gray information of original images. Then,the distance weighted interpolation method was used to calculate the transformation function and enhanced the various regions in different degrees. After that,the histogram of enhanced image was corrected. Finally,the epipolar constraint method was used in the image matching experiment. The results show that,because of the enhanced image gray value gradient difference,there exists some extent of increased matching success rate and uniformity in the woodland area which has smaller gray change,thus favoring the smooth progress of the work of subsequent image pro- cessing.

Decision Support Using Anesthesia Information Management System Records and Accreditation Council for Graduate Medical Education Case Logs for Resident Operating Room Assignments

Our goal in this study was to develop decision support systems for resident operating room (OR) assignments using anesthesia information management system (AIMS) records and Accreditation Council for Graduate Medical Education (ACGME) case logs and evaluate the implementations. We developed 2 Web-based systems: an ACGME case-log visualization tool, and Residents Helping in Navigating OR Scheduling (Rhinos), an interactive system that solicits OR assignment requests from residents and creates resident profiles. Resident profiles are snapshots of the cases and procedures each resident has done and were derived from AIMS records and ACGME case logs. A Rhinos pilot was performed for 6 weeks on 2 clinical services. One hundred sixty-five requests were entered and used in OR assignment decisions by a single attending anesthesiologist. Each request consisted of a rank ordered list of up to 3 ORs. Residents had access to detailed information about these cases including surgeon and patient name, age, procedure type, and admission status. Success rates at matching resident requests were determined by comparing requests with AIMS records. Of the 165 requests, 87 first-choice matches (52.7%), 27 second-choice matches (16.4%), and 8 third-choice matches (4.8%) were made. Forty-three requests were unmatched (26.1%). Thirty-nine first-choice requests overlapped (23.6%). Full implementation followed on 8 clinical services for 8 weeks. Seven hundred fifty-four requests were reviewed by 15 attending anesthesiologists, with 339 first-choice matches (45.0%), 122 second-choice matches (16.2%), 55 third-choice matches (7.3%), and 238 unmatched (31.5%). There were 279 overlapping first-choice requests (37.0%). The overall combined match success rate was 69.4%. Separately, we developed an ACGME case-log visualization tool that allows individual resident experiences to be compared against case minimums as well as resident peer groups. We conclude that it is feasible to use ACGME case-log data in decision support systems for informing resident OR assignments. Additional analysis will be necessary to assess the educational impact of these systems.

SU‐E‐J‐72: Shift Invariant Feature Transform (SIFT) Based Image Stitching for Panoramic Cone Beam CT (CBCT)

Purpose: Panoramic CBCT is a novel imaging technique that stitches together projection images from multiple views to increase the imaging volume to as large as practically needed using half (200 degree gantry rotation) scans only. In this study, we investigated a SIFT‐based method to improve the accuracy of image stitching for panoramic CBCT. Methods: Panoramic CBCT data were acquired for a torso phantom using two half scans: (A) the detector at the center position and (B) the detector shifted 148mm toward the right side of the phantom. For each projection image of scan A, a corresponding projection image of the same gantry angle was interpolated for scan B using images of two neighboring gantry angles. The SIFT method was applied to extract ‘matching’ feature points in the overlapping region of the projection images of the same gantry angle from each scan. The rigid (translation and rotation) transform matrix derived from this analysis was then used to stitch together the two projection images for CBCT reconstruction using the simultaneous algebraic reconstruction technique (SART) method. Three overlapping (5‐cm, 3‐cm and 2‐cm) sizes were used for the SIFT analysis to determine the optimal imaging parameters. Results: The CBCT reconstructions using the SIFT stitching method showed significant artifact reduction compared with the direct stitching method. The success rate of matching (less than 0.5 degrees rotation and 2 pixels horizontal/vertical shifts) was close to 100% for 5‐cm overlapping and gradually reduced as the overlapping size decreased. The minimum overlapping size we could reliably apply our method was 2 cm (93.8% success rate) below which significant operator involvement was required to determine the applicable rigid transform parameters. Conclusion: We have demonstrated the effectiveness of the SIFT stitching method for panoramic CBCT reconstruction. We are currently improving the registration technique to further reduce the required overlapping size. This work was partially supported by a DOD grant DOD W81XWH1010862

Ghost publications in the pediatric surgery match

IntroductionPediatric surgery fellowship is considered one of the most competitive subspecialties in medicine. With fierce competition increasing the stakes, publications and first authorship are paramount to the success rate of matching. We analyzed Electronic Residency Application Service applications for verification of authorship to determine rate of misrepresentation. MethodsAfter institutional review board approval, the bibliographies of fellowship applications from 2007–2009 were reviewed to allow time for publication. Only peer-reviewed journal articles were evaluated. A Medline search was conducted for the article, by author or by title. If the article could not be found, other authors and journal were used as search parameters. If the article was still not found, the website for the journal was searched for abstract or manuscript. Finally, an experienced medical sciences librarian was consulted for remaining unidentified articles. Differences between misrepresented and accurate applications were analyzed, including: age, gender, medical and undergraduate school parameters, advanced degrees, other fellowships, number of publications, first author publications, American Board of Surgery In-Training Examination scores, and match success. ResultsThere were 147 applications reviewed. Evidence of misrepresentation was found in 17.6% of the applicants (24/136), with 34 instances in 785 manuscripts (4.3%). Manuscripts classified as published were verified 96.7% of the time, were not found in 1.4%, and had incorrect authors or journal in less than 1% each. “In press” manuscripts were verified 88.3% of the time, 6.4% could not be found, and 4.3% had an incorrect journal listing. Number of publications (P = 0.026) and first author publications (P = 0.037) correlated with misrepresentation. None of the remaining variables was significant. ConclusionsThe pediatric surgical pool has a very low incidence of suspicious citations; however, authorship claims should be verified.

Positioning performance evaluation of magnetic contour matching under different accuracy of sensor

The accuracy of geomagnetic reference map, geomagnetic sensor, and inertial navigation system is the key factor which affects the reliability of magnetic contour matching (MAGCOM) system. In order to improve the reliability of MAGCOM, the influence of the sensor's accuracy on the matching success rate has been studied. For different geomagnetic reference maps, the factors and their physical mechanism affecting matching success rate have been analyzed, the factors are geomagnetic sensor error, velocity error, and heading angle error. The error range of sensors was determined by the simulation computing which was based on a practical system and a simulation experimentation was implemented by using the geomagnetic reference map. The simulation results show that MAGCOM can allow the velocity error 0.14 m/s, the heading angle error 0.6 and the standard deviation of geomagnetic sensor noise 11 nT, when the matching success rate is 90%.

Nonlinear intensity difference correlation for multi-temporal remote sensing images

Compared to geometric distortions exhibited in remote sensing images, radiometric deformations are less addressed in the literature and linear variations are usually assumed during image matching or registration. This paper proposes a novel robust and automatic image matching approach for multi-temporal and multi-sensor remote sensing images which usually present non-linear radiometric changes. We introduce a non-linear intensity difference correlation (NIDC) algorithm that aims to reduce the impacts of non-linear intensity differences during image matching. Differences of illumination intensity are accounted for and modeled in the NIDC algorithm through the extension of traditional feature-based matching techniques. Our proposed approach has been tested with typical multi-temporal and multi-sensor remote sensing images characterized by either dense or sparse ground control points (GCPs). Experimental results demonstrate that our matching approach outperforms common image matching techniques such as cross correlation (CC), scale-invariant feature transform (SIFT), and speeded-up robust features (SURF) with respects to matching success rate and robustness in test data.

Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking

Observations of ice motion are critical for constraining ice sheet mass balance and contribution to sea level rise, as well as predicting future changes. A wealth of imagery now exists for measuring ice motion from space, but existing repeat-image feature-tracking (RIFT) algorithms require the selection of several location- and data-specific parameters and manual data editing and are therefore not efficient for processing large numbers of image pairs for differing regions. Here, we present the multiple-image/multiple-chip RIFT algorithm which does not involve any user-defined local/empirical parameters and has a higher matching success rate than conventional single-image single-chip correlation matching. We also present an efficient method for applying RIFT to null-value striped data, such as the Landsat-7 Enhanced Thematic Mapper Plus. This method offers the potential for fully automated processing of large data sets.