Abstract
Transmitting image data without losing significant information is challenging for any network application especially when large color images are transmitted through TCP communication protocol. This is due to network limitations such as buffer overflow, underflow and network traffic flow etc. This paper presents a new method for image size reduction such that the network can transmit data without much loss of information, and hence, quality. The proposed method obtains bit planes for the color input images, which results in eight binary planes. Unlike the existing bit plane based image size reduction methods, which assume that the most significant plane or some other planes contain useful information, the proposed method finds the plane that contains dominant information automatically. For each plane, the proposed method explores the saliency that finds dominant information based on Markov Chain Process and similarity estimation between neighbor pixels. To reduce computational burden, we use Canny edge maps of the saliency of the planes for feature extraction. We propose to explore ring-growing concept for the edge maps to study the spatial distribution of saliency, locally. The proposed method detects the plane based on statistics of saliency distribution. To validate the step of plane detection, we estimate transmission error caused during data transmission through TCP communication protocol for the images at sending and receiving ends. Experimental results on plane detection show that the proposed method is better than the existing methods in terms of detection rate. Our experiments on image transmission through TCP communication protocol show that the proposed method outperforms the existing methods in terms of error estimation and quality analysis. Furthermore, experiments are conducted to analyze packet loss in terms of number of duplicate acknowledgements and retransmission during packets transmission for the color, edge and plane to show that transmitting plane images improves network performance in terms of less number of duplicate acknowledgement, retransmission and time taken in seconds.
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This research work was supported by the Faculty of Computer Science and Information Technology, University of Malaya under a special allocation of Post Graduate Funds for the RP036B-15AET and PG063-2016 A project.
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Kaljahi, M.A., Shivakumara, P., Hakak, S. et al. Saliency-based bit plane detection for network applications. Multimed Tools Appl 79, 18495–18513 (2020). https://doi.org/10.1007/s11042-020-08741-9
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DOI: https://doi.org/10.1007/s11042-020-08741-9