Automatic Matching Algorithm Research Articles

A novel meshless method for numerical simulation of fractured-vuggy reservoirs

This paper proposes a novel meshless numerical simulation method for fractured-vuggy reservoirs. Initially, model discretization involves extracting fracture and vug feature nodes along the contours of the reservoir bodies and in alignment with fracture orientations, tailored to the characteristics of the fractured-vuggy oil deposit. Subsequently, a connection element model is established within the influence domain. Based on the seepage equations of the connection system, a computational method for the parameters of the connection elements (connection transmissibility and connection volume) is defined. In addition, a sequential method is employed to solve for the pressure and saturation, achieving rapid prediction of the reservoir's production dynamics. On this basis, an automatic history matching algorithm is utilized for real-time fitting of oil–water dynamic indicators, inverting the characteristic parameters of the connection element model, and quantitatively characterizing the injection–production connection elements. The research findings indicate that the method is capable of rapidly fitting and predicting the dynamics of oil reservoir production. Furthermore, conceptual model examples have substantiated that it achieves comparable computational efficiency and superior computational accuracy when compared to the traditional finite difference (volume) method under the same nodal conditions. Additionally, the node arrangement for fractures and vugs is comparatively flexible, and it can ensure the integrity of the flow paths with a limited number of nodes to enhance predictive accuracy. Therefore, this method can effectively meet the rapid prediction requirements for fractured-vuggy reservoirs and also provides a novel meshless computational approach for the numerical simulation of such reservoirs.

Set-up errors of the neck are underestimated using the overall registration frame of head and neck in IMRT for NPC.

There is no standardized registration frame of cone beam CT (CBCT) in intensity modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC). The overall registration frame that covers the whole head and neck is the most commonly used CBCT registration frame for NPC patients in IMRT. To compare the set-up errors using different registration frames of CBCT for NPC to assess the set-up errors for different region of the commonly used clinical overall registration frame. 294 CBCT images of 59 NPC patients were collected. Four registration frames were used for matching. The set-up errors were obtained using an automatic matching algorithm and then compared. The expansion margin from the clinical target volume (CTV) to the planned target volume (PTV) in the four groups was also calculated. The average range of the isocenter translation and rotation errors of four registration frames are 0.89∼2.41 mm and 0.49∼1.53°, respectively, which results in a significant difference in the set-up errors (p < 0.05). The set-up errors obtained from the overall frame are smaller than those obtained from the head, upper neck, and lower neck frames. The margin ranges of the overall, head, upper neck, and lower neck frames in three translation directions are 1.49∼2.39 mm, 1.92∼2.45 mm, 1.86∼3.54 mm and 3.02∼4.78 mm, respectively. The expansion margins calculated from the overall frame are not enough, especially for the lower neck. Set-up errors of the neck are underestimated by the overall registration frame. Thus, it is important to improve the position immobilization of the neck, especially the lower neck. The margin of the target volume of the head and neck region should be expanded separately if circumstances permit.

An iterative framework with active learning to match segments in road networks

ABSTRACT Road network matching that detects arc-to-arc relations is a crucial prerequisite for the update of road data. The increasing complexity of multi-source and multi-scale road network data challenges the existing methods on accuracy and efficiency. This paper focuses on the interactive-based probabilistic relaxation approach. It is difficult to obtain satisfactory results by using completely automatic matching algorithm in some complicated road networks such as multi-lane carriageways. We try to improve the matching accuracy by combining optimization matching model with manual interaction. The method uses the module of active learning to construct unlabeled sample pool from preliminary matching of probabilistic relaxation, and then selects the arcs with the highest uncertainty by query function. The selected road is then handed over to humans to determine its arc-to-arc relations in the other road network. Finally, the matching parameters are automatically adjusted according to the user’s feedback information, so as to realize the dynamic optimization of the model. Our interaction method is efficient as it only needs to specify few arc-to-arc mappings and others can be amended automatically. Our experimental results reveal that active learning can substantially improve the performance of standard probabilistic relaxation algorithms in road network matching.

Toward Robust Partial-Image Based Template Matching Techniques for MRI-Guided Interventions.

We have developed an MRI-safe needle guidance toolkit for MRI-guided interventions intended to enable accurate positioning for needle-based procedures. The toolkit allows intuitive and accurate needle angulation and entry point positioning according to an MRI-based plan, using a flexible, patterned silicone 2D grid. The toolkit automatically matches the grid on MRI planning images with a physical silicon grid placed conformally on the patient's skin and provides the Interventional Radiologist an easy-to-use guide showing the needle entry point on the silicon grid as well as needle angle information. The radiologist can use this guide along with a 2-degree-of-freedom (rotation and angulation relative to the entry point) hand-held needle guide to place the needle into the anatomy of interest. The initial application that we are considering for this toolkit is arthrography, a diagnostic procedure to evaluate the joint space condition. However, this toolkit could be used for any needle-based and percutaneous procedures such as MRI-guided biopsy and facet joint injection. For matching the images, we adopt a transformation parameter estimation technique using the phase-only correlation method in the frequency domain. We investigated the robustness of this method against rotation, displacement, and Rician noise. The algorithm was able to successfully match all the dataset images. We also investigated the accuracy of identifying the entry point from registered template images as a prerequisite for a future targeting study. Application of the template matching algorithm to locate the needle entry points within the MRI dataset resulted in an average entry point location estimation accuracy of 0.12 ±0.2 mm. This promising result motivates a more detailed assessment of this algorithm in the future including a targeting study on a silicon phantom with embedded plastic targets to investigate the end-to-end accuracy of this automatic template matching algorithm in the interventional MRI room.

2021 Census to Census Coverage Survey Matching Results.

The 2021 England and Wales Census was matched to the Census Coverage Survey (CCS). This was an essential requisite for estimating undercount in the Census. To ensure outputs could be produced within a year of census day, matching had to be completed in eight weeks.&#x0D; We used the Data Access Platform to write efficient and accurate automatic matching algorithms. Probabilistic and associative matching methods were used to present candidate pairs that could not be automatically matched but likely consisted of many true matches. These were resolved by matchers in the clerical matching system. Active learning was used to iteratively improve probabilistic parameters as matches were made.&#x0D; We also developed a pre-search algorithm that simplifies clerical matching by replacing clerical searching (here’s a record, can you find a match?) with clerical resolution (here are two records, do they match?).&#x0D; As a result of our improvements, we increased our automatic matching rates from 70% (2011 Census) to 93% (2021 Census) for person matching and from 60% to 95% for household matching, without loss of accuracy. Precision and recall were estimated to both be 99.96% for person matching and 100% and 99.78% respectively for household matching. For both persons and households, the same trends seen in 2011 are seen here too; however, most of the biases have decreased and most match rates have increased.&#x0D; Dual system estimation using the matched and unmatched records enabled us to estimate that coverage in the 2021 England and Wales Census was 97%.&#x0D; The matching methodology implemented for the 2021 Census to CCS matching improved both person and household matching greatly when compared with the 2011 matching. The clerical matching system enabled clerical matching at scale and at pace. Thus, we successfully completed all clerical matching within our eight-week deadline.

Automated scripting of the dosimetric evaluation of adaptive versus non-adaptive radiotherapy

Objective. To quantify the benefit of adaptive radiotherapy over non-adaptive radiotherapy it is useful to extract and compare dosimetric features of patient treatments in both scenarios. This requires Image-Guided Radiotherapy (IGRT) matching of baseline planning to adaptive fraction imaging, followed by extraction of relevant dose metrics. This can be impractical to retrospectively perform manually for multiple patients. Approach. Here we present an algorithm for automatic IGRT matching of baseline planning with fraction imaging and performing automated dosimetric feature extraction from adaptive and non-adaptive treatment plans, thereby allowing comparison of the two scenarios. This workflow can be done in an entirely automated way via scripting solutions given structure and dose Digital Imaging and Communications in Medicine (DICOM) files from baseline and adaptive fractions. We validate this algorithm against the results of manual IGRT matching. We also demonstrate automated dosimetric feature extraction. Lastly, we combine these two scripting solutions to extract daily adaptive and non-adaptive radiotherapy dosimetric features from an initial cohort of patients treated on an MRI guided linear accelerator (MR-LINAC). Results. Our results demonstrate that automated feature extraction and IGRT matching was successful and comparable to results performed by a manual operator. We have therefore demonstrated a method for easy analysis of patients treated on an adaptive radiotherapy platform. Significance. We believe that this scripting solution can be used for quantifying the benefits of adaptive therapy and for comparing adaptive therapy against various non-adaptive IGRT scenarios (e.g. 6 degree of freedom couch rotation).

Устройство компенсации провалов напряжения с накопителем энергии и функцией безударного перевода нагрузки

This work is devoted to the development of a simulation model of a voltage drop compensation device containing an electric energy storage device. The proposed control algorithm makes it possible to minimize the shock moment and the current surge of the motor when transferring the load in the event of an emergency. The control system considered in the work implements an algorithm for automatic phase matching of the EMF of the motor and the voltage of the inverter, which allows soft switching function transferring the load from one power source to another. In this case, the electric voltage angle of the inverter is phase-consistent with the decrease EMF of the motor. The calculation of EMF with the allocation of amplitude, phase and frequency is carried out with the help of an observer developed by the authors. As a result, a workable simulation model of a high-speed automatic reserve input device with an energy storage device was obtained. In conclusion, the authors cite transients that confirm the operability of the proposed approaches.

Integrated Photogrammetric and Photoclinometric Processing of Multiple HRSC Images for Pixelwise 3-D Mapping on Mars

Images from the high-resolution stereo camera (HRSC) is an important data source for retrieving 3-D information of the Martian surface. Photogrammetry has been widely applied to HRSC images to generate digital elevation models (DEMs). However, in circumstances of insufficient textures or severe atmospheric influences on Mars, photogrammetry may fail to generate DEMs of favorable quality. Besides, photogrammetry is not able to recover pixelwise geometrical information. Meanwhile, photoclinometry is a promising method to retrieve pixelwise 3-D information from image intensities. Few works in the past have explored the appropriate use of photoclinometry for HRSC data. This article presents an innovative approach of integrating photogrammetry and photoclinometry for pixelwise 3-D mapping of the Martian surface using multiple HRSC images. First, an effective photogrammetric strategy is developed to process multiple HRSC images. For images influenced by haze or aerosol problems, an automatic object-based matching algorithm is formulated to compensate for obvious flaws on the disparity map. Second, multiview photoclinometry considering atmospheric effect is developed to refine the photogrammetric DEM to pixel resolution. Qualitative and quantitative validations are conducted using two representative sets of HRSC images and compared with the reference data. The results show that the generated DEMs have good geometric consistency with the reference data, but offer subtle topographic details conforming to the original images. The proposed method provides a promising solution to exploit the HRSC images for 3-D mapping of the Martian surface with better resolution and coverage, which is of significance for future Mars exploration missions and scientific research.

An automatic image matching algorithm based on thin plate splines

There are substantial problems in the photogrammetric image matching especially in the images taken by UAVs in the regions where grassland, waterfront, forest, buildings, bridges, high-voltage lines etc. in the urban and rural areas. The main reason of these problems are color, tone, texture, contrast and scale changes cannot be successfully detected in between sequential images. To solve these problems, radial basis functions can be used. The thin plate spline (TPS) that has a natural representation in terms of radial basis functions is used as a non-rigid transformation model in image matching. In other words, TPS is strong interpolation method for coordinate transformations modeling. In this study, the Istanbul Technical University Campus was selected as the study area and the study focused on using the integration of SURF and TPS, called as automatic TPS (A-TPS), for photogrammetric matching of UAV images obtained for the campus. Three different test areas that have different surface characteristics were selected and the implementation of A-TPS realized using control points on these test areas. The A-TPS algorithm was compared with SURF and VisualSFM software that uses the SIFTGPU method. Also, the images were rotated 45 degrees and the same operations were repeated. RANSAC algorithm was applied to determine the inliers from the point matches obtained from all methods. The A-TPS algorithm performs better than the other two methods, especially for images with the homogenous texture of forestry areas.

Towards Automatic Points of Interest Matching

Complementing information about particular points, places, or institutions, i.e., so-called Points of Interest (POIs) can be achieved by matching data from the growing number of geospatial databases; these include Foursquare, OpenStreetMap, Yelp, and Facebook Places. Doing this potentially allows for the acquisition of more accurate and more complete information about POIs than would be possible by merely extracting the information from each of the systems alone. Problem: The task of Points of Interest matching, and the development of an algorithm to perform this automatically, are quite challenging problems due to the prevalence of different data structures, data incompleteness, conflicting information, naming differences, data inaccuracy, and cultural and language differences; in short, the difficulties experienced in the process of obtaining (complementary) information about the POI from different sources are due, in part, to the lack of standardization among Points of Interest descriptions; a further difficulty stems from the vast and rapidly growing amount of data to be assessed on each occasion. Research design and contributions: To propose an efficient algorithm for automatic Points of Interest matching, we: (1) analyzed available data sources—their structures, models, attributes, number of objects, the quality of data (number of missing attributes), etc.—and defined a unified POI model; (2) prepared a fairly large experimental dataset consisting of 50,000 matching and 50,000 non-matching points, taken from different geographical, cultural, and language areas; (3) comprehensively reviewed metrics that can be used for assessing the similarity between Points of Interest; (4) proposed and verified different strategies for dealing with missing or incomplete attributes; (5) reviewed and analyzed six different classifiers for Points of Interest matching, conducting experiments and follow-up comparisons to determine the most effective combination of similarity metric, strategy for dealing with missing data, and POIs matching classifier; and (6) presented an algorithm for automatic Points of Interest matching, detailing its accuracy and carrying out a complexity analysis. Results and conclusions: The main results of the research are: (1) comprehensive experimental verification and numerical comparisons of the crucial Points of Interest matching components (similarity metrics, approaches for dealing with missing data, and classifiers), indicating that the best Points of Interest matching classifier is a combination of random forest algorithm coupled with marking of missing data and mixing different similarity metrics for different POI attributes; and (2) an efficient greedy algorithm for automatic POI matching. At a cost of just 3.5% in terms of accuracy, it allows for reducing POI matching time complexity by two orders of magnitude in comparison to the exact algorithm.

An integrated approach for global profiling of multi-type constituents: Comprehensive chemical characterization of Lonicerae Japonicae Flos as a case study

To fully capture the chemo-diversity of medicinal plants is very essential for understanding of their pharmacological activities and guiding scientific quality control. Aiming to facilitate chemical characterization and novel natural products discovery, the present study proposed an integrated approach based on two-dimensional liquid chromatography coupled with quadrupole-Orbitrap mass spectrometer (2D LC/Q-Orbitrap MS). An offline comprehensive two-dimensional (2D) LC system was constructed to cover and separate multi-type constituents by combining hydrophilic interaction chromatography (HILIC) and conventional reversed phase C18. A two-step mass defect filtering-induced exclusion list-data dependent acquisition was developed to increase MS/MS coverage and selectivity. Additionally, an efficient interpretation strategy, combining an automatic matching algorithm and molecular networking (MN), was introduced for rapid recognition of known compounds and efficient elucidation of unreported ones. As a case study, the integrated approach was tentatively applied for comprehensive characterization of complex multi-type components in Lonicerae Japonicae Flos (LJF), a traditional Chinese medicine. Consequently, a total of 537 compounds were characterized from LJF, including a large number of potential novel structures. It was demonstrated that the integrated approach is powerful in deep investigation on chemical diversity of medicinal plants and discovery of novel structures. Its application could also be extended for global profiling of other complicated chemical systems, such as Chinese medicinal formulas.

Automatic matching of computed tomography and stereolithography data

Background and ObjectiveComputed tomography (CT) is one of the most frequently used medical imaging methods. An important application area of CT is dental implants, which require precise inspection and analysis of oral structures. Since CT provides a precise 3D model of the teeth, bones and nerves, it can be used as a surgical guide for dental implants. Along with CT, optical 3D images called stereolithography (STL) have also been widely used. STL images obtained from optical 3D images can be used to show the 3D surfaces of oral structures. Since CT data and STL data deploy different technologies to obtain dental information, we can obtain more accurate dental implants by combining the two datasets. Since the two datasets are acquired by using different sensors, the datasets need to be registered. MethodsAn automatic matching algorithm is proposed for CT and STL image registration, which is based on depth maps and maximum intensity projection. Then, fine tuning was performed based on volume matching. ResultsWhen applied to real-world databases, the proposed method provided an average matching error of 2.7 mm for the upper jaw and 2.3 mm for the lower jaw with an average processing time of about 19 s. ConclusionsThe proposed method performs accurate registration of CT and STL.

Ablation of ventricular arrhythmia originating at the papillary muscle using an automatic pacemapping module

Ventricular arrhythmia originating from the papillary muscle (VA-PM) is characterized by multiple exits and morphologic alternations. The conventional ablation strategy relies on activation mapping, but the results might be suboptimal. The purpose of this study was to propose a novel pacemapping strategy aimed at multiple exits using high-output software as a complementary approach to the conventional strategy. A consecutive 13 patients with VA-PM were enrolled in this study. Novel pacemapping based on an automatic matching algorithm and integrated electroanatomic mapping was used to quantify the morphology variation in these patients and to identify the potential exits of VA-PM. Complementary ablation targeting at the best matching site of each morphology was performed. Twelve of 13 patients (92%) experienced morphologic alternation, and a total of 34 morphologies were detected (2.6 ± 1.0 per patient). A total of 23 (68%) morphologies were detected as spontaneous pleomorphic ventricular premature complexes (VPCs) before procedure, and 4 morphologies (12%) were induced under isoproterenol infusion. Another 7 of 34 morphologies (21%) could be found only after radiofrequency ablation attempts. Exits with a high pacemapping correlation index for corresponding morphology would be mapped, so preferential exits could be identified. Mean interexit distance was 15.1 ± 5.9 mm. Acute success rate was 100%. During mean follow-up of 12.2 ± 6.9 months, only 1 case recurred with ventricular tachycardia. Although 3 cases recurred with different VPC morphologies, the VPC burden decreased from 16.3% ± 8.8% to 2.6% ± 1.7%. This novel pacemapping strategy could effectively eliminate multiple exits as a complementary approach to the conventional strategy.

ROLE OF TIE-POINTS DISTRIBUTION IN AERIAL PHOTOGRAPHY

Abstract. Automatic image matching algorithms, and especially feature-based methods, profoundly changed our understanding and requirements of tie points. The number of tie points has increased by orders of magnitude, yet the notions of accuracy and reliability of tie points remain equally important. The spatial distribution of tie points is less predictable, and is subject only to limited control. Feature-based methods also highlighted a conceptual division of the matching process into two separate stages – feature extraction and feature matching. In this paper we discuss whether spatial distribution requirements, such as Von Gruber positions, are still relevant to modern matching methods. We argue that forcing such patterns might no longer be required in the feature extraction stage. However, we claim spatial distribution is important in the feature matching stage. We will focus on terrains that are notorious for difficult matching, such as water bodies, with real data obtained by users of VisionMap’s A3 Edge camera and LightSpeed photogrammetric suite.

ROLE OF TIE-POINTS DISTRIBUTION IN AERIAL PHOTOGRAPHY

Automatic image matching algorithms, and especially feature-based methods, profoundly changed our understanding and requirements of tie points. The number of tie points has increased by orders of magnitude, yet the notions of accuracy and reliability of tie points remain equally important. The spatial distribution of tie points is less predictable, and is subject only to limited control. Feature-based methods also highlighted a conceptual division of the matching process into two separate stages – feature extraction and feature matching. &amp;lt;br&amp;gt;&amp;lt;br&amp;gt; In this paper we discuss whether spatial distribution requirements, such as Von Gruber positions, are still relevant to modern matching methods. We argue that forcing such patterns might no longer be required in the feature extraction stage. However, we claim spatial distribution is important in the feature matching stage. &amp;lt;br&amp;gt;&amp;lt;br&amp;gt; We will focus on terrains that are notorious for difficult matching, such as water bodies, with real data obtained by users of VisionMap’s A3 Edge camera and LightSpeed photogrammetric suite.

A New Efficient Calibration Method for Binocular Camera

In the vision 3-D measurement field, camera calibration results directly affect the accuracy of measurement. So camera calibration method is hot spot in this field. This paper proposes a new efficient calibration method with binocular camera. First, the method uses an accurate extraction algorithm to extract the ellipse center of calibration target image. Second, the paper presents a automatic matching algorithm based RANSAC (RANSAC SAMPLE CONSENSUS), the automatic matching algorithm is simple, fast, and can complete space calibration feature points matching its image point at once. At the beginning of matching, sort calibration points in the target according to a certain sequence. The sequence of feature points extracted in the calibration image does not correspond with one of the feature points in calibration target, because of the camera distortion. But obtain the correct matching points by the RANSAC algorithm. According to the camera calibration model, use the correct matching points and obtain correct intrinsic and extrinsic parameters of each camera and the relative parameters of two cameras. Finally, through experimental verification, the results show that the calibration method is fast and robust, and has higher calibration accuracy.

Estimation of pseudo relative permeability curves for a heterogeneous reservoir with a new automatic history matching algorithm

Abstract Reliable relative permeability curves are important for successful reservoir simulation and modeling. These curves may be available on fine scale models. However, detailed descriptions demand a huge amount of memory and processing time. Therefore, it is needed to upscale core-size relative permeability curves measured by laboratory experiments to a scale suitable for the various types of simulation. This upscaling is accomplished with pseudo functions. In this work, a new automatic history matching algorithm based on B-spline representation was applied to estimate pseudo relative permeability curves. The performance of the generated pseudo curves were compared with four dynamic pseudo functions for a 3D heterogeneous water-flooding case. In addition, the effect of the pseudo function estimation uncertainty on the cumulative oil production was investigated after 10 years of production. Results revealed that relative permeability curves obtained from history matching gives the best performance among other pseudos and this methodology can be used for reservoir simulation over periods beyond that of the original match.

Importance of Distributed Temperature Sensor Data for Steam Assisted Gravity Drainage Reservoir Characterization and History Matching Within Ensemble Kalman Filter Framework

Distributed temperature sensing (DTS), an optical fiber down-hole monitoring technique, provides a continuous and permanent well temperature profile. In steam assisted gravity drainage (SAGD) reservoirs, the DTS plays an important role to provide depth-and-time continuous temperature measurement for steam management and production optimization. These temperature observations provide useful information for reservoir characterization and shale detection in SAGD reservoirs. However, use of these massive data for automated SAGD reservoir characterization has not been investigated. The ensemble Kalman filter (EnKF), a parameter estimation approach using these real-time temperature observations, provides a highly attractive algorithm for automatic history matching and quantitative reservoir characterization. Due to its complex geological nature, the shale barrier exhibits as a different facies in sandstone reservoirs. In such reservoirs, due to non-Gaussian distributions, the traditional EnKF underestimates the uncertainty and fails to obtain a good production data match. We implemented discrete cosine transform (DCT) to parameterize the facies labels with EnKF. Furthermore, to capture geologically meaningful and realistic facies distribution in conjunction with matching observed data, we included fiber-optic sensor temperature data. Several case studies with different facies distribution and well configurations were conducted. In order to investigate the effect of temperature observations on SAGD reservoir characterization, the number of DTS observations and their locations were varied for each study. The qualities of the history-matched models were assessed by comparing the facies maps, facies distribution, and the root mean square error (RMSE) of the predicted data mismatch. Use of temperature data in conjunction with production data demonstrated significant improvement in facies detection and reduced uncertainty for SAGD reservoirs. The RMSE of the predicted data is also improved. The results indicate that the assimilation of DTS data from nearby steam chamber location has a significant potential in significant reduction of uncertainty in steam chamber propagation and production forecast.

Comparing Proposed Signature with SURF in Object Detection Process

ABSTRACTMost object detection and classification algorithms only locate regions in the image, whether they are within a template-sliding mask or in interested region blobs. However, such regions may be ambiguous, especially when the object of interest is very small or unclear. This paper proposes an algorithm for automatic object detection and matching based on its own signature using morphological segmentation tools. Moreover, the algorithm tries to match objects, not in object blobs or regions of interest, but among the constructed proposed object signatures. During the matching process, the SURF method makes a comparison of process between its matching performance and the proposed matching process on all experimental objects. The process has tested a wide variety of 120 dissimilar objects; it has achieved 100% of constructed signatures, and it has achieved 96% of correct object matching; whereas SURF has achieved only 85% for all tested objects.

A novel 3D vorticity based approach for automatic registration of low resolution range images

This paper tackles the problem of feature matching and range image registration. Our approach is based on a novel set of discriminating three-dimensional (3D) local features, named 3D-Vor (Vorticity). In contrast to conventional local feature representation techniques, which use the vector field (i.e. surface normals) to just construct their local reference frames, the proposed feature representation exploits the vorticity of the vector field computed at each point of the local surface to capture the distinctive characteristics at each point of the underlying 3D surface. The 3D-Vor descriptors of two range images are then matched using a fully automatic feature matching algorithm which identifies correspondences between the two range images. Correspondences are verified in a local validation step of the proposed algorithm and used for the pairwise registration of the range images. Quantitative results on low resolution Kinect 3D data (Washington RGB-D dataset) show that our proposed automatic registration algorithm is accurate and computationally efficient. The performance evaluation of the proposed descriptor was also carried out on the challenging low resolution Washington RGB-D (Kinect) object dataset, for the tasks of automatic range image registration. Reported experimental results show that the proposed local surface descriptor is robust to resolution, noise and more accurate than state-of-the-art techniques. It achieves 90% registration accuracy compared to 50%, 69.2% and 52% for spin image, 3D SURF and SISI/LD-SIFT descriptors, respectively.