Three-Dimensional Map Generation From Side-Scan Sonar Images

1990 ◽  
Vol 112 (2) ◽  
pp. 96-102 ◽  
Author(s):  
J. M. Cuschieri ◽  
M. Hebert
Keyword(s):  
Remote Sensing ◽  
Three Dimensional ◽  
Map Building ◽  
Side Scan Sonar ◽  
Essential Components ◽  
Map Generation ◽  
Sonar Systems ◽  
Sonar Images ◽  
Direct Generation

The generation of three-dimensional (3-D) images and map building are essential components in the development of an autonomous underwater system. Although the direct generation of 3-D images is more efficient than the recovery of 3-D data from 2-D information, at present for underwater applications where sonar is the main form of remote sensing, the generation of 3-D images can only be achieved by either complex sonar systems or with systems which have a rather low resolution. In this paper an overview is presented on the type of sonar systems that are available for underwater remote sensing, and then a technique is presented which demonstrates how through simple geometric reasoning procedures, 3-D information can be recovered from side scan-type (2-D) data. Also presented is the procedure to perform map building on the estimated 3-D data.

Acoustic Remote Sensing in Maritime Archaeology

2012 ◽  
Author(s):  
Rory Quinn
Keyword(s):  
Remote Sensing ◽  
Maritime Archaeology ◽  
Site Formation ◽  
Data Sets ◽  
Side Scan Sonar ◽  
Single Beam ◽  
Acoustic Data ◽  
Sonar Systems ◽  
Acoustic Remote Sensing ◽  
Reconnaissance Surveys

This article offers an introduction to acoustic remote sensing. In shipwreck studies, acoustic remote sensing has traditionally been used for reconnaissance surveys and for site relocation. With the advent of higher-resolution sonar systems, the focus in shipwreck studies has shifted toward site reconstruction and studies of site formation. Acoustic systems provide baseline data at rates higher than those of experienced dive teams. This article describes how acoustic data is generated. It describes the profiling methods such as single-beam echo-sounders and sub-bottom profilers, and swath methods such as side-scan sonar and multibeam echo-sounders. The last few years have seen developments of multielement sonar platforms, which allow for the acquisition of true concurrent sonar data sets from one platform. Every phase of development in sonar technology brings an increase in sensors' resolving capability and therefore the ability to image smaller and smaller artifacts in greater detail.

scholarly journals Remote sensing techniques in the search for ancient shipwrecks: how to distinguish a wreck from a rock in geophysical recordings

2007 ◽  
Vol 40 (4) ◽  
pp. 1845 ◽  
Author(s):  
D. Sakellariou
Keyword(s):  
Remote Sensing ◽  
Shallow Water ◽  
Deep Water ◽  
Geophysical Methods ◽  
Geological Structure ◽  
Archaeological Research ◽  
Marine Geology ◽  
Side Scan Sonar ◽  
Sonar Images ◽  
Remote Sensing Techniques

This paper presents the way conventional marine geophysical methods may be used with the highest efficiency for deep-water archaeological research, especially for the detection of ancient shipwrecks. Their use becomes all the more effective, when the principles of oceanography and marine geology are being followed during the interpretation of the geophysical recordings. The integration of sub-bottom profiling data provides valuable information on the geological structure of the seafloor 's shallow substrate, which are an almost absolute prerequisite for a geologically reasonable interpretation of the side scan sonar images. Otherwise, interpretation of the sonar recordings may be erroneous or may be in direct discrepancy with the shallow sub-seafloor geological structure. Limitations of the efficiency of the geophysical methods in the case of targets of biogenic or anthropogenic origin or in shallow water environments are also being discussed

scholarly journals Optimizing the Sediment Classification of Small Side-Scan Sonar Images Based on Deep Learning

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 29416-29428
Author(s):  
Xiaoming Qin ◽  
Xiaowen Luo ◽  
Ziyin Wu ◽  
Jihong Shang
Keyword(s):  
Deep Learning ◽  
Side Scan Sonar ◽  
Sediment Classification ◽  
Sonar Images ◽  
Small Side

scholarly journals Mathematical models for information classification and recognition of multi-target optical remote sensing images

Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 951-960
Author(s):  
Haiqing Zhang ◽  
Jun Han
Keyword(s):  
Remote Sensing ◽  
Recognition Rate ◽  
Three Dimensional ◽  
Remote Sensing Image ◽  
Optical Remote Sensing ◽  
Specific Class ◽  
Three Dimensional Model ◽  
Image Information ◽  
Information Classification ◽  
Optical Remote Sensing Image

Abstract Traditionally, three-dimensional model is used to classify and recognize multi-target optical remote sensing image information, which can only identify a specific class of targets, and has certain limitations. A mathematical model of multi-target optical remote sensing image information classification and recognition is designed, and a local adaptive threshold segmentation algorithm is used to segment multi-target optical remote sensing image to reduce the gray level between images and improve the accuracy of feature extraction. Remote sensing image information is multi-feature, and multi-target optical remote sensing image information is identified by chaotic time series analysis method. The experimental results show that the proposed model can effectively classify and recognize multi-target optical remote sensing image information. The average recognition rate is more than 95%, the maximum robustness is 0.45, the recognition speed is 98%, and the maximum time-consuming average is only 14.30 s. It has high recognition rate, robustness, and recognition efficiency.

Automatic tourist attraction and representative icon determination for tourist map generation

2013 ◽  
Vol 13 (1) ◽  
pp. 18-28 ◽  
Author(s):  
Chao-Hung Lin ◽  
Jyun-Yuan Chen ◽  
Shun-Siang Hsu ◽  
Yun-Huan Chung
Keyword(s):  
User Study ◽  
Three Dimensional ◽  
Automatic Generation ◽  
Visual Features ◽  
Tourist Attraction ◽  
Tourist Attractions ◽  
Photo Sharing ◽  
Map Generation ◽  
Three Dimensional Models ◽  
Better Than

Tourist maps are designed to direct tourists to tourist attractions in unfamiliar areas. A well-designed tourist map can provide tourists with sufficient and intuitive information about places of interest. Thus, providing up-to-date information on places of interest and selecting their representative icons are fundamental and important in automatic generation of tourist maps. In this article, approaches for determining places of interest and for determining their representative icons are introduced. In contrast to general digital tourist maps that use text, simple shapes, or three-dimensional models, we use photos that offer abundant visual features of places of interest as icons in tourist maps. The photos are automatically extracted from a repository of photos downloaded from photo-sharing communities. Tourist attractions and their corresponding image icons are determined by means of photo voting and photo quality assessment. Qualitative analyses, including a user study and experiments in several areas with numerous tourist attractions, indicated that the proposed method can generate visually pleasant and elaborate tourist maps. In addition, the analyses indicated that the map produced by our method is better than maps generated by related methods and is comparable to hand-designed tourist maps.

Prevalence of Toenail Onychomycosis in Patients with Type 2 Diabetes Mellitus and Evaluation of Risk Factors

2011 ◽  
Vol 101 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Aynur Gulcan ◽  
Erim Gulcan ◽  
Sukru Oksuz ◽  
Idris Sahin ◽  
Demet Kaya
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Fasting Blood Glucose ◽  
Diabetic Patients ◽  
Essential Components ◽  
Patients With Diabetes ◽  
Epidemiologic Risk

Background: We sought to determine the frequency of toenail onychomycosis in diabetic patients, to identify the causative agents, and to evaluate the epidemiologic risk factors. Methods: Data regarding patients’ diabetic characteristics were recorded by the attending internal medicine clinician. Clinical examinations of patients’ toenails were performed by a dermatologist, and specimens were collected from the nails to establish the onycomycotic abnormality. All of the specimens were analyzed by direct microscopy and culture. Results: Of 321 patients with type 2 diabetes mellitus, clinical onychomycosis was diagnosed in 162; 41 of those diagnoses were confirmed mycologically. Of the isolated fungi, 23 were yeasts and 18 were dermatophytes. Significant correlations were found between the frequency of onychomycosis and retinopathy, neuropathy, obesity, family history, and duration of diabetes. However, no correlation was found with sex, age, educational level, occupation, area of residence, levels of hemoglobin A1c and fasting blood glucose, and nephropathy. The most frequently isolated agents from clinical specimens were yeasts. Conclusions: Long-term control of glycemia to prevent chronic complications and obesity and to promote education about the importance of foot and nail care should be essential components in preventing onychomycosis and its potential complications, such as secondary foot lesions, in patients with diabetes mellitus. (J Am Podiatr Med Assoc 101(1): 49–54, 2011)

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