An Overview of Various Template Matching Methodologies in Image Processing

Swaroop, P. R. S.; Sharma, Neelam

doi:10.5120/ijca2016912165

Cited by 41 publications

(22 citation statements)

References 1 publication

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“…However, their approach is tested on high-textured surfaces. Moreover, to the best of our knowledge, the template matching requires more computational time than the features-based approaches, provides less accurate results and it is not rotation invariant [48][49][50], even though a direct comparison of the template matching using our acquired data has not been done yet.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

Patruno

Colella

Nitti

et al. 2020

Sensors

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In this paper we tackle the problem of indoor robot localization by using a vision-based approach. Specifically, we propose a visual odometer able to give back the relative pose of an omnidirectional automatic guided vehicle (AGV) that moves inside an indoor industrial environment. A monocular downward-looking camera having the optical axis nearly perpendicular to the ground floor, is used for collecting floor images. After a preliminary analysis of images aimed at detecting robust point features (keypoints) takes place, specific descriptors associated to the keypoints enable to match the detected points to their consecutive frames. A robust correspondence feature filter based on statistical and geometrical information is devised for rejecting those incorrect matchings, thus delivering better pose estimations. A camera pose compensation is further introduced for ensuring better positioning accuracy. The effectiveness of proposed methodology has been proven through several experiments, in laboratory as well as in an industrial setting. Both quantitative and qualitative evaluations have been made. Outcomes have shown that the method provides a final positioning percentage error of 0.21% on an average distance of 17.2 m. A longer run in an industrial context has provided comparable results (a percentage error of 0.94% after about 80 m). The average relative positioning error is about 3%, which is still in good agreement with current state of the art.

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Section: Discussion Of Resultsmentioning

confidence: 99%

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

Patruno

Colella

Nitti

et al. 2020

Sensors

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“…The No. 2 CCD collects images which show the tool tip and the tool-setting plane and adopts a template matching algorithm [ 30 , 31 ] to identify the tool tip. The corresponding tool tip templates are set for different tools, and the matching results preliminarily locate the tool position.…”

Section: Calibration Of Visual Tool-setting Systemmentioning

confidence: 99%

Computer Vision Tool-Setting System of Numerical Control Machine Tool

Hou

Zhang

Yang

2020

Sensors

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An automatic tool-setting and workpiece online detecting system was proposed to study the key technologies of next-generation intelligent vision computerized numerical control (CNC) machines. A computer vision automatic tool-setting system for a CNC machine was set up on the basis of the vision tool-setting principle. A rapid vision calibration method based on the position feedback from the CNC machine was proposed on the basis of the theory of traditional vision system calibration. The coordinate mapping relationship of the image and the CNC machine, the tool-setting mark point on the workpiece, and the tool tip were calibrated. The vision system performance testing and system calibration experiments were performed. Experimental results indicated that the time consumption was 128 ms in image processing. The precision of tool setting and measuring was less than 1 μm. The workpiece positioning and processing online detection function of the system can completely meet the requirements of visual CNC machine application, and the system has wide application prospects.

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“…Template matching methods categorized as Featured-based (FB) approach, Area-based (AB) approach, Template-based (TB) approach and motion-tracking & Occlusion Handling [11].…”

Section: A) Template Matching Approachesmentioning

confidence: 99%

Automated Tele-Health Monitoring System for Animal Health using Image Processing

B*,

Reddy B*,

Priya

et al. 2020

IJRTE

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For effective livestock management identification and control of parasites and bacteria is a challenging factor. Parasites, worms and bacteria has a huge hazard to the health of animals, which can harm the gastrointestinal tract, and result in decreased propagative routine, diminished development rates, less yield in terms of meat, fiber and milk, even leads to death of the animals, which in turn causing health problems for human society also. A proper knowledge of animal parasites by identification of them and application of the proper antibiotic or vaccine in appropriate dosage will improve the quality of the livestock and its byproducts leading to the more profits to the farmer. The livestock farms are located at the remote places and the communication between the veterinary doctor to the farmer is poor, took long time and expensive. This can be overcome by utilization of the digital technology and automation of the process which can be handled by a layman at the field to provide electronic information for both e-prescription for intermediate treatment and the information to the expert at the remote location for proper diagnosis and validation of the electronic prescription. Digital image processing of the microscopic pictures with high resolution cameras from the samples of the animals will provide a platform for automation of the process. The detection of the parasites and its stages can be done by denoising the images, segmentation of the parasites, templating the images for isolation of parasites and bacteria by comparing them with preloaded data of different types of parasites and their different stages leads to the identification of parasites, bacteria and giving the electronic prescription within a short period then the diagnosed report can be sent to the expert for validation.In the present paper the authors have proposed a smart system for telemonitoring and mobile health management system.

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An Overview of Various Template Matching Methodologies in Image Processing

Cited by 41 publications

References 1 publication

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

A Vision-Based Odometer for Localization of Omnidirectional Indoor Robots

Computer Vision Tool-Setting System of Numerical Control Machine Tool

Automated Tele-Health Monitoring System for Animal Health using Image Processing

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