A fast template matching algorithm based on principal orientation difference

Jiao, Jichao; Wang, Xin; Deng, Zhongliang; Cao, Jun; Tang, Wei‐Hua

doi:10.1177/1729881418778223

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…This reduces the robustness of these techniques for dense urban environments. To overcome this problem, Jiao et al proposed a camera pose estimation system using both a skyline-matching and a GPS method for urban AR applications [61]. Skyline features can model the general geometric characteristic of a street in a geo-tagged image and yield the yaw angle when matched with the skyline extracted from the GIS.…”

Section: Edge-based Trackingmentioning

confidence: 99%

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems

Sadeghi‐Niaraki

Choi

2020

Sensors

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Most existing augmented reality (AR) applications are suitable for cases in which only a small number of real world entities are involved, such as superimposing a character on a single surface. In this case, we only need to calculate pose of the camera relative to that surface. However, when an AR health or environmental application involves a one-to-one relationship between an entity in the real-world and the corresponding object in the computer model (geo-referenced object), we need to estimate the pose of the camera in reference to a common coordinate system for better geo-referenced object registration in the real-world. New innovations in developing cheap sensors, computer vision techniques, machine learning, and computing power have helped to develop applications with more precise matching between a real world and a virtual content. AR Tracking techniques can be divided into two subcategories: marker-based and marker-less approaches. This paper provides a comprehensive overview of marker-less registration and tracking techniques and reviews their most important categories in the context of ubiquitous Geospatial Information Systems (GIS) and AR focusing to health and environmental applications. Basic ideas, advantages, and disadvantages, as well as challenges, are discussed for each subcategory of tracking and registration techniques. We need precise enough virtual models of the environment for both calibrations of tracking and visualization. Ubiquitous GISs can play an important role in developing AR in terms of providing seamless and precise spatial data for outdoor (e.g., environmental applications) and indoor (e.g., health applications) environments.

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Section: Edge-based Trackingmentioning

confidence: 99%

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems

Sadeghi‐Niaraki

Choi

2020

Sensors

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“…The method showed better results. Jichao Jiao et al [12] proposed a fast template matching algorithm, based on principal orientation difference feature. Edge direction was identified and different features are extracted from template.…”

Section: Mp Sukassini Tvelmuruganmentioning

confidence: 99%

Ascertaining Abnormal Regions in Mammogram Images using Gravitational Search Local Map View Technique

Sukassini¹,

Velmurugan²

2019

IJITEE

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Segmentation of mammogram images has gained importance in many medical treatments and diagnostic processes. Mammogram image segmentation aims at correctly separating different tissues, organs, or pathologies in volumetric image data. Most of the existing algorithms for image segmentation have a "scattered" cluster problem (disconnected clusters) happened in many clustering techniques (agglomerative, k-means, Dbscan) . Above algorithms not taken into account of both quality value and connectivity of points and region varying shapes. Two methods are proposed in this paper. The first technique is LMV (Local Map View) and the second technique is GSLMV (Gravitational Search Local Map View). LMV concentrates on determination of local quality for each point in all instances of the region in the comparative similarity view by applying the initial cluster technique. This view allows the user to choose instances for detailed analysis and filter the outlier instances from the input, next specific feature selection process identifies regions with systematic characteristics across the images. In this research work, pixels in groups with high intensity are assumed to be abnormal regions in cancer and non-cancer images. Fuzzy clustering is used to cluster the pixels. The optimal threshold from GS are initialized as cluster centres. This increases the speed of GSLMV algorithm. Performances of GSA, LMV and GSLMV methods are measured using False Rejection Rate, pixel count, Peak signal to noise ratio and runtime metrics. GSLMV showed better results based on pixel count, PSNR and runtime.

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“…However, it only adopts the image tone information. Jiao et al [22] divided the target region into 24 circular areas in 8 directions. The feature of each circular area at the same scale is calculated by Census transform and rotated according to the main direction.…”

Section: Related Workmentioning

confidence: 99%

Shape Matching Based on Multi-Scale Invariant Features

Zhang

Xin-guo

2019

IEEE Access

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Shape matching has been extensively used in various fields. The local feature-based or global feature-based algorithms can hardly describe the shape comprehensively due to their inherent defects. Combining the local and global feature to describe the shape has become a trend. In this paper, an improved discrete curve evolution algorithm is proposed which combines the discrete curve evolution with the uniform sampling and achieves a better description of the shape contour. Three simple and intuitive multi-scale features which represent both the global and local features of shapes are designed from aspects of the spatial relationship of contour points, structural information of contour sequence, and shape geometry feature. A cyclic Smith-Waterman algorithm is introduced to solve local contour matching and starting point selection. Experimental results demonstrate that our proposed features are translation, rotation, and scaling invariant, and have good robustness to deformation. Retrieval accuracies of Kimia99, Kimai216, and MPEG-7 indicate that our method can bring out a better performance. INDEX TERMS Shape matching, improved discrete curve evolution, multi-scale invariant features, cyclic Smith-Waterman algorithm. I. INTRODUCTION

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A fast template matching algorithm based on principal orientation difference

Cited by 10 publications

References 25 publications

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems

A Survey of Marker-Less Tracking and Registration Techniques for Health & Environmental Applications to Augmented Reality and Ubiquitous Geospatial Information Systems

Ascertaining Abnormal Regions in Mammogram Images using Gravitational Search Local Map View Technique

Shape Matching Based on Multi-Scale Invariant Features

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