Low-power focal-plane dynamic texture segmentation based on programmable image binning and diffusion hardware

Jorge Fernández-Berni; Ricardo Carmona-Galán

doi:10.1117/12.822590

20 May 2009 Low-power focal-plane dynamic texture segmentation based on programmable image binning and diffusion hardware

Jorge Fernández-Berni, Ricardo Carmona-Galán

Author Affiliations +

Proceedings Volume 7365, Bioengineered and Bioinspired Systems IV; 736502 (2009) https://doi.org/10.1117/12.822590
Event: SPIE Europe Microtechnologies for the New Millennium, 2009, Dresden, Germany

Abstract

Stand-alone applications of vision are severely constrained by their limited power budget. This is one of the main reasons why vision has not yet been widely incorporated into wireless sensor networks. For them, image processing should be suscribed to the sensor node in order to reduce network traffic and its associated power consumption. In this scenario, operating the conventional acquisition-digitization-processing chain is unfeasible under tight power limitations. A bio-inspired scheme can be followed to meet the timing requirements while maintaining a low power consumption. In our approach, part of the low-level image processing is conveyed to the focal-plane thus speeding up system operation. Moreover, if a moderate accuracy is permissible, signal processing is realized in the analog domain, resulting in a highly efficient implementation. In this paper we propose a circuit to realize dynamic texture segmentation based on focal-plane spatial bandpass filtering of image subdivisions. By the appropriate binning, we introduce some constrains into the spatial extent of the targeted texture. By running time-controlled linear diffusion within each bin, a specific band of spatial frequencies can be highlighted. Measuring the average energy of the components in that band at each image bin the presence of a targeted texture can be detected and quantified. The resulting low-resolution representation of the scene can be then employed to track the texture along an image flow. An application specific chip, based on this analysis, is being developed for natural spaces monitoring by means of a network of low-power vision systems.

Citation Download Citation

Jorge Fernández-Berni and Ricardo Carmona-Galán "Low-power focal-plane dynamic texture segmentation based on programmable image binning and diffusion hardware", Proc. SPIE 7365, Bioengineered and Bioinspired Systems IV, 736502 (20 May 2009); https://doi.org/10.1117/12.822590

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KEYWORDS

Diffusion

Image filtering

Image segmentation

Spatial frequencies

Capacitors

Filtering (signal processing)

Image processing

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