Hierarchical Template Matching Research Articles

Multi-pyramid-based hierarchical template matching for 6D pose estimation in industrial grasping task

PurposeTemplate matching is one of the most suitable choices for full six degrees of freedom pose estimation in many practical industrial applications. However, the increasing number of templates while dealing with a wide range of viewpoint changes results in a long runtime, which may not meet the real-time requirements. This paper aims to improve matching efficiency while maintaining sample resolution and matching accuracy.Design/methodology/approachA multi-pyramid-based hierarchical template matching strategy is proposed. Three pyramids are established at the sphere subdivision, radius and in-plane rotation levels during the offline template render stage. Then, a hierarchical template matching is performed from the highest to the lowest level in each pyramid, narrowing the global search space and expanding the local search space. The initial search parameters at the top level can be determined by the preprocessing of the YOLOv3 object detection network to further improve real-time performance.FindingsExperimental results show that this matching strategy takes only 100 ms under 100k templates without loss of accuracy, promising for real industrial applications. The authors further validated the approach by applying it to a real robot grasping task.Originality/valueThe matching framework in this paper improves the template matching efficiency by two orders of magnitude and is validated using a common template definition and viewpoint sampling methods. In addition, it can be easily adapted to other template definitions and viewpoint sampling methods.

Identifying Myocardial Infarction Using Hierarchical Template Matching-Based Myocardial Strain: Algorithm Development and Usability Study.

BackgroundMyocardial infarction (MI; location and extent of infarction) can be determined by late enhancement cardiac magnetic resonance (CMR) imaging, which requires the injection of a potentially harmful gadolinium-based contrast agent (GBCA). Alternatively, emerging research in the area of myocardial strain has shown potential to identify MI using strain values.ObjectiveThis study aims to identify the location of MI by developing an applied algorithmic method of circumferential strain (CS) values, which are derived through a novel hierarchical template matching (HTM) method.MethodsHTM-based CS H-spread from end-diastole to end-systole was used to develop an applied method. Grid-tagging magnetic resonance imaging was used to calculate strain values in the left ventricular (LV) myocardium, followed by the 16-segment American Heart Association model. The data set was used with k-fold cross-validation to estimate the percentage reduction of H-spread among infarcted and noninfarcted LV segments. A total of 43 participants (38 MI and 5 healthy) who underwent CMR imaging were retrospectively selected. Infarcted segments detected by using this method were validated by comparison with late enhancement CMR, and the diagnostic performance of the applied algorithmic method was evaluated with a receiver operating characteristic curve test.ResultsThe H-spread of the CS was reduced in infarcted segments compared with noninfarcted segments of the LV. The reductions were 30% in basal segments, 30% in midventricular segments, and 20% in apical LV segments. The diagnostic accuracy of detection, using the reported method, was represented by area under the curve values, which were 0.85, 0.82, and 0.87 for basal, midventricular, and apical slices, respectively, demonstrating good agreement with the late-gadolinium enhancement–based detections.ConclusionsThe proposed applied algorithmic method has the potential to accurately identify the location of infarcted LV segments without the administration of late-gadolinium enhancement. Such an approach adds the potential to safely identify MI, potentially reduce patient scanning time, and extend the utility of CMR in patients who are contraindicated for the use of GBCA.

Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation

Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers.

A Novel Hierarchical Template Matching Model for Cardiac Motion Estimation

Cardiovascular disease diagnosis and prognosis can be improved by measuring patient-specific in-vivo local myocardial strain using Magnetic Resonance Imaging. Local myocardial strain can be determined by tracking the movement of sample muscles points during cardiac cycle using cardiac motion estimation model. The tracking accuracy of the benchmark Free Form Deformation (FFD) model is greatly affected due to its dependency on tunable parameters and regularisation function. Therefore, Hierarchical Template Matching (HTM) model, which is independent of tunable parameters, regularisation function, and image-specific features, is proposed in this article. HTM has dense and uniform points correspondence that provides HTM with the ability to estimate local muscular deformation with a promising accuracy of less than half a millimetre of cardiac wall muscle. As a result, the muscles tracking accuracy has been significantly (p < 0.001) improved (30%) compared to the benchmark model. Such merits of HTM provide reliably calculated clinical measures which can be incorporated into the decision-making process of cardiac disease diagnosis and prognosis.

Internal‐to‐internal transition method for consecutive hierarchical template matching

This study proposes a method reducing the tree traversal cost by first investigating the most probable node instead of the root node when a hierarchical template matching is consecutively applied to the object. In particular, this study gives a novel viewpoint that a consecutive hierarchical template matching could be regarded as a transition of a hierarchical finite state machine, and then it proposes a novel method considering the transitions between the internal nodes of the hierarchical template tree. The proposed method is verified by applying it to pedestrian silhouette detection.

Motion Complexity Analysis with Automated Lung Field Tracking in MRI Temporal Sequences

AbstractWe propose a new method for evaluating the lung field motion complexity in magnetic resonance (MR) image temporal sequences, where complexity is defined as the minimum number of respiratory movement patterns to represent the detected lung field motion. In the first part of this work, a method for high precision landmark determination and tracking on a temporal sequences of chest magnetic resonance images is proposed. The landmark determination and tracking algorithms are based on a hierarchical template matching algorithm. A stable matching is made with some additional rules to avoid mistracking. In the second part of this work, the optimum respiratory movement patterns are determined by minimizing the mean square error applied to the determined paths. The proposed algorithm was tested with 29 subjects, including healthy subjects and COPD (Chronic Obstructive Pulmonary Disease) patients. The paths obtained by the landmark tracking algorithm represent the movement of some parenchyma internal structures. The paths automatically obtained were analyzed and compared to paths manually obtained by a medical specialist. It is concluded that the respiratory movement patterns necessary to represent the paths determined manually and automatically for the same subjects were compatible. The results also show that COPD patients have two main respiratory movement patterns. Copyright©2011 IFAC.

Finding regions of interest for cancerous masses enhanced by elimination of linear structures and considerations on detection correctness measures in mammography

Cancerous mass detection methods for mammographic images still miss some malignant cases on the one hand, and produce too many false-positive (FP) detections with respect to the number of true-positive (TP) detections on the other. An attempt has been described to improve the TP ratio per image and to decrease the number of FP errors in the hierarchical template matching detector of regions of interest (ROIs) for cancerous masses by eliminating the images of linear structures (LSs) from the mammograms. The LSs were detected with an accumulation-based line detector. The measure of correctness of the ROIs detection was discussed and the quality of the detector, represented by free receiver operating characteristics curves, was compared with the human-eye observations. The result is that the widely used measure of detection correctness seems to underestimate the detection quality made by a human. Tests were performed on the mammograms from the MIAS database.

Template matching in pyramids

Correlation of a small “template” array with a large image array is an operation commonly used in image analysis. Edge detection, line and corner finding are some applications of the technique. Two problems with template matching are its computational cost and its sensitivity to noise. Pyramids (image hierarchies incorporating variable resolution) allow template matching to be performed in a new manner. Hierarchical template matching allows both a savings in computation time (by a problem-dependent amount) and a considerable degree of insensitivity to noise. These techniques are introduced and analyzed through a series of simple and empirical examples. An important feature of template matching locations that would be difficult to enforce and evene to express, in the traditional nonhierarchical framework. The hierarchical approach admits a large variety of image-processing operations.