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A new image size reduction model for an efficient visual sensor network

Kaljahi, Maryam Asadzadeh and Shivakumara, Palaiahnakote and Idris, Mohd Yamani Idna and Anisi, Mohammad Hossein and Blumenstein, Michael (2019) 'A new image size reduction model for an efficient visual sensor network.' Journal of Visual Communication and Image Representation, 63. p. 102573. ISSN 1047-3203

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Image size reduction for energy-efficient transmission without losing quality is critical in Visual Sensor Networks (VSNs). The proposed method finds overlapping regions using camera locations, which eliminate unfocussed regions from the input images. The sharpness for the overlapped regions is estimated to find the Dominant Overlapping Region (DOR). The proposed model partitions further the DOR into sub-DORs according to capacity of the cameras. To reduce noise effects from the sub-DOR, we propose to perform a Median operation, which results in a Compressed Significant Region (CSR). For non-DOR, we obtain Sobel edges, which reduces the size of the images down to ambinary form. The CSR and Sobel edges of the non-DORs are sent by a VSN. Experimental results and a comparative study with the state-of-the-art methods shows that the proposed model outperforms the existing methods in terms of quality, energy consumption and network lifetime.

Item Type: Article
Uncontrolled Keywords: Visual sensor network; Image size reduction; Inter-redundancy; Intra-redundancy; Energy consumption; Quality of the image
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 29 Jul 2019 11:43
Last Modified: 15 Jan 2022 01:28

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