Underwater cable automatic recognition using Hough transformation

Chao Chen; Masayuki Nakajima

doi:10.1117/12.205529

27 March 1995 Underwater cable automatic recognition using Hough transformation

Chao Chen, Masayuki Nakajima

Proceedings Volume 2423, Machine Vision Applications in Industrial Inspection III; (1995) https://doi.org/10.1117/12.205529
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

In this paper, we make an attempt to predict the location of a cable in next frame according to some parameters in current frame. At first, the initial condition is that the approximate location of cable must be given. From Hough Transformation, a high accumulated degree point in Hough Space is gotten. Afterwards, by inverse Hough Transformation, using that point, the location is detected and then cable is pointed out from its original image. Based on actual working conditions and performance indices, as well as the location in current frame, the maximum range of degree within which the cable may occur in next frame with high possibility is evaluated. Furthermore, a narrow range of location in next frame is confirmed according to the speed of robot. It is this narrow range that reduces the influence of the background on the detected object to the least. Therefore, the location of cable can be detected more accurately. Still more, as the final target of this project, an approach to detect the dangerous status of Cable is shown. In this approach, we want to distinguish the predict area into three parts with a simple area partition. By means of time sequence, the relative changes on the size of area which is between shadow and cable can conclude whether the cable is suspended in water.

Citation Download Citation

Chao Chen and Masayuki Nakajima "Underwater cable automatic recognition using Hough transformation", Proc. SPIE 2423, Machine Vision Applications in Industrial Inspection III, (27 March 1995); https://doi.org/10.1117/12.205529

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available