English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/107663
COMPARTIR / IMPACTO:
Estadísticas
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Título

Focal-Plane Sensing-Processing: A Power-Efficient Approach for the Implementation of Privacy-Aware Networked Visual Sensors

AutorFernández-Berni, J. ; Carmona-Galán, R. ; Río, Rocío del; Kleihorst, R.; Philips, Wilfried; Rodríguez-Vázquez, Ángel
Palabras claveVisual sensor networks
Internet of Thongs (IoT)
Privacy
Security
Vision sensors
Focal-plane processing
Obfuscation
Pixelation
Granular space
Feature extraction
Fecha de publicación2014
EditorMultidisciplinary Digital Publishing Institute
CitaciónSensors, 14: 15203-15216 (2014)
ResumenThe capture, processing and distribution of visual information is one of the major challenges for the paradigm of the Internet of Things. Privacy emerges as a fundamental barrier to overcome. The idea of networked image sensors pervasively collecting data generates social rejection in the face of sensitive information being tampered by hackers or misused by legitimate users. Power consumption also constitutes a crucial aspect. Images contain a massive amount of data to be processed under strict timing requirements, demanding high-performance vision systems. In this paper, we describe a hardware-based strategy to concurrently address these two key issues. By conveying processing capabilities to the focal plane in addition to sensing, we can implement privacy protection measures just at the point where sensitive data are generated. Furthermore, such measures can be tailored for efficiently reducing the computational load of subsequent processing stages. As a proof of concept, a full-custom QVGA vision sensor chip is presented. It incorporates a mixed-signal focal-plane sensing-processing array providing programmable pixelation of multiple image regions in parallel. In addition to this functionality, the sensor exploits reconfigurability to implement other processing primitives, namely block-wise dynamic range adaptation, integral image computation and multi-resolution filtering. The proposed circuitry is also suitable to build a granular space, becoming the raw material for subsequent feature extraction and recognition of categorized objects.
Versión del editorhttp://dx.doi.org/10.3390/s140815203
URIhttp://hdl.handle.net/10261/107663
DOI10.3390/s140815203
Aparece en las colecciones: (IMSE-CNM) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
Sensors_2014.pdf3,49 MBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 

Artículos relacionados:


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.