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Advances in Mechanical Engineering
Volume 2013 (2013), Article ID 426810, 8 pages
Research Article

Improved Visual Hook Capturing and Tracking for Precision Hoisting of Tower Crane

School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received 12 April 2013; Accepted 27 May 2013

Academic Editor: Liang Gong

Copyright © 2013 Yanming Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


To maintain safe operation of the tower crane, it is important to monitor the activities of the hook system. Visual monitoring and image recognition are the optimum methods for crane hook tracking and precision hoisting. High real-time performance and low computation requirements are required for tower crane hook capturing and tracking system which is implemented on the embedded Advanced RISC Machines (ARM) processor or Microcontrol Unit (MCU). Using the lift rope of a tower crane as the target object, a new high-performance hook tracking method suitble for ARM processor or MCU applications is presented. The features of the lifting process are analyzed, and an improved progressive probabilistic Hough transform (IPPHT) algorithm is proposed which can reduce capturing time by up to 80%. Combining color histogram with a binary search algorithm, an adaptive zooming method for precise hoisting is presented. Using this method the optimum zoom scale can be achieved within a few iterations.