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Wireless vision sensor networks (WVSNs) have a number of wireless vision sensor nodes (VSNs), often spread over a large geographical area. Each node has an image capturing unit, a battery or alternative energy source, a memory unit, a light source, a wireless link, and a processing unit. The challenges associated with WVSNs include low energy consumption, low bandwidth, limited memory, and processing capabilities. In order to meet these challenges, our paper is focused on the exploration of energy-efficient reconfigurable architectures for VSN. In this paper, the design and research challenges associated with the implementation of VSN on different computational platforms, such as microcontroller, field-programmable gate arrays, and server, are explored. In relation to this, the effect on the energy consumption and the design complexity at the node, when the functionality is moved from one platform to another, are analyzed. Based on the implementation of the VSN on embedded platforms, the lifetime of the VSN is predicted using the measured energy values of the platforms for different implementation strategies. The implementation results show that an architecture, where the compressed images after pixel-based operation are transmitted, realize a WVSN system with low energy consumption. Moreover, the complex postprocessing tasks are moved to a server which has less constraints.