Paper
26 October 2016 Software for hyperspectral, joint photographic experts group (.JPG), portable network graphics (.PNG) and tagged image file format (.TIFF) segmentation
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Abstract
This paper presents a system developed by an application of a neural network Multilayer Perceptron for drone acquired agricultural image segmentation. This application allows a supervised user training the classes that will posteriorly be interpreted by neural network. These classes will be generated manually with pre-selected attributes in the application. After the attribute selection a segmentation process is made to allow the relevant information extraction for different types of images, RGB or Hyperspectral. The application allows extracting the geographical coordinates from the image metadata, geo referencing all pixels on the image. In spite of excessive memory consume on hyperspectral images regions of interest, is possible to perform segmentation, using bands chosen by user that can be combined in different ways to obtain different results.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. S. Bruno, B. P. Rodrigo, and A. de C. Jorge Lucio "Software for hyperspectral, joint photographic experts group (.JPG), portable network graphics (.PNG) and tagged image file format (.TIFF) segmentation", Proc. SPIE 10008, Remote Sensing Technologies and Applications in Urban Environments, 1000815 (26 October 2016); https://doi.org/10.1117/12.2242156
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Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Neural networks

RGB color model

Hyperspectral imaging

Visualization

Software development

Eye models

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