Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/92714
Title: Comparative analysis of methods for the log boundaries isolation
Authors: Kruglov, A. V.
Chiryshev, Y. V.
Issue Date: 2015
Publisher: SciTePress
Citation: Kruglov A. V. Comparative analysis of methods for the log boundaries isolation / A. V. Kruglov, Y. V. Chiryshev. — DOI 10.5220/0005552703570361 // ICINCO 2015 - 12th International Conference on Informatics in Control, Automation and Robotics, Proceedings. — 2015. — Iss. 2. — P. 357-361.
Abstract: The scrutiny of boundaries isolation methods is presented in this paper. The newly developed algorithms, based on regression analysis and integral projection are compared with Hough transform in order to analyze their effectiveness for the specific problem of moving logs control. The comparative analysis of the methods was carried out on the database of images obtained from video sequence of real industrial process by the criteria of accuracy and operation speed. Results of the test show that the line-by-line scanning method with posterior LOWESS regression analysis has the best accuracy. However, the best appropriate for the implementation in the real-time control systems based on machine vision technology is consecutive line selection method due to its reasonable accuracy and impressive performance.
Keywords: BOUNDARY DETECTION
HOUGH TRANSFORM
IMAGE PROCESSING
INTEGRAL PROJECTION
REGRESSION ANALYSIS
COMPUTER CONTROL SYSTEMS
FEATURE EXTRACTION
HOUGH TRANSFORMS
IMAGE PROCESSING
REAL TIME CONTROL
REGRESSION ANALYSIS
ROBOTICS
BOUNDARY DETECTION
COMPARATIVE ANALYSIS
INDUSTRIAL PROCESSS
INTEGRAL PROJECTIONS
OPERATION SPEED
REASONABLE ACCURACY
SPECIFIC PROBLEMS
VIDEO SEQUENCES
IMAGE ANALYSIS
URI: http://elar.urfu.ru/handle/10995/92714
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 84943514975
WOS ID: 000380619000050
PURE ID: 290767
ISBN: 9789897581236
DOI: 10.5220/0005552703570361
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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