You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact

Algorithms for the Detection of First Bottom Returns and Objects in the Water Column in Side-Scan Sonar Images



Mohammed Al-Rawi , Fredrik Elmgren , Mirgita Frasheri , Baran Çürüklü, Xin Yuan , José-Fernán Martínez-Ortega, Joaquim Bastos , Jonathan Rodriguez , Marc Pinto

Research group:

Publication Type:

Conference/Workshop Paper


OCEANS '17 A Vision for our Marine Future


Underwater imaging has become an active research area in recent years as an effect of increased interest in underwater environments and is getting potential impact on the world economy, in what is called blue growth. Since sound propagates larger distances than electromagnetic waves underwater, sonar is typically used for underwater imaging. One interesting sonar image setting is comprised of using two parts (left and right) and is usually referred to as sidescan sonar. The image resulted from sidescan sonars, which is called waterfall image, usually has to distinctive parts, the water column and the image seabed. Therefore, the edge separating these two parts, which is called the first bottom return, is the real distance between the sonar and the seabed bottom (which is equivalent to sensor primary altitude). The sensory primary altitude can be measured if the imaging sonar is complemented by interferometric sonar, however, simple sonar systems have no way to measure the first bottom returns other than signal processing techniques. In this work, we propose two methods to detect the first bottom returns; the first is based on smoothing cubic spline regression and the second is based on a moving average filter to detect signal variations. The results of both methods are compared to the sensor primary altitude and have been successful in 22 images out of 25.


author = {Mohammed Al-Rawi and Fredrik Elmgren and Mirgita Frasheri and Baran {\c{C}}{\"u}r{\"u}kl{\"u} and Xin Yuan and Jos{\'e}-Fern{\'a}n Mart{\'\i}nez-Ortega and Joaquim Bastos and Jonathan Rodriguez and Marc Pinto},
title = {Algorithms for the Detection of First Bottom Returns and Objects in the Water Column in Side-Scan Sonar Images},
month = {June},
year = {2017},
booktitle = {OCEANS '17 A Vision for our Marine Future},
url = {}