Development of an acousto-optic system for hyperspectral image segmentation

• Published in: Metrology and Measurement systems Vol. 26; no. 3; p. 517
• Main Authors: Isaza, César, Mosquera, Julio M, Gómez-Méndez, Gustavo A, Zavala-De Paz, Jonny P, Karina-Anaya, Ely, Rizzo-Sierra, José A, Palillero-Sandoval, Omar
• Format: Journal Article
• Language: English
• Published: Warsaw Polish Academy of Sciences 01-01-2019
• Subjects: acousto-optic system; Acousto-optics; Algorithms; CCD cameras; Computer vision; Digital imaging; Engineering research; Hyperspectral imaging; Image analysis; Image segmentation; Neural networks; Optics; Remote sensing; Spectrum analysis; Subtraction; Tomography
• DOI: 10.24425/mms.2019.129576
• EISSN: 2300-1941
• ISSN: 2080-9050

Image segmentation is a typical operation in many image analysis and computer vision applications. However, hyperspectral image segmentation is a field which have not been fully investigated. In this study an analogue- digital image segmentation technique is presented. The system uses an acousto-optic tuneable filter, and a CCD camera to capture hyperspectral images that are stored in a digital grey scale format. The data set was built considering several objects with remarkable differences in the reflectance and brightness components. In addition, the work presents a semi-supervised segmentation technique to deal with the complex problem of hyperspectral image segmentation, with its corresponding quantitative and qualitative evaluation. Particularly, the developed acousto-optic system is capable to acquire 120 frames through the whole visible light spectrum. Moreover, the analysis of the spectral images of a given object enables its segmentation using a simple subtraction operation. Experimental results showed that it is possible to segment any region of interest with a good performance rate by using the proposed analogue-digital segmentation technique.