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Assessing the impact of JPEG compression on the semantic segmentation of agricultural images

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Abstract

Compression is a important issue when dealing with large amounts of data. We can reduce the size of a file by eliminating data, what is called lossy compression. In an image file, the eliminated data can be small details present in the scene which the compression algorithm deems expendable, without any consideration on how these data will be used posteriorly. Inspired by the work proposed in Zanjani et al. (J Med Imaging 6(2):027501, 2019), this paper aims to evaluate whether the application of a lossy compression method can affect negatively the segmentation of agricultural images obtained using neural networks. For this purpose, we applied a customized version of the U-Net neural network to the crop row segmentation problem. Results show that the application of JPEG compression is feasible for agricultural images, obtaining Dice coefficient results above 0.750 for the most difficult cases, and an average of 0.951, even for images with a compression of  95%.

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Acknowledgements

André R. Backes gratefully acknowledges the financial support of CNPq (National Council for Scientific and Technological Development, Brazil) (Grant #307100/2021-9). João Batista Ribeiro gratefully acknowledges the financial support of Fapemig (Fundação de Amparo à Pesquisa do Estado de Minas Gerais). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) – Finance Code 001.

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Authors and Affiliations

  1. School of Computer Science, Federal University of Uberlândia, Uberlândia, MG, 38408-100, Brazil

    Jocival Dantas Dias Júnior & João Batista Ribeiro

  2. Department of Computing, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil

    André Ricardo Backes

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  1. Jocival Dantas Dias Júnior
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  2. João Batista Ribeiro
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Contributions

J. D. Dias Junior and J. B. Ribeiro performed the experiments. J. B. Ribeiro and A. R. Backes prepared figures. A. R. Backes supervised the work. J. B. Ribeiro and A. R. Backes wrote the main manuscript text. All authors reviewed the manuscript.

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Correspondence to André Ricardo Backes.

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Júnior, J.D.D., Ribeiro, J.B. & Backes, A.R. Assessing the impact of JPEG compression on the semantic segmentation of agricultural images. SIViP 18, 9–15 (2024). https://doi.org/10.1007/s11760-023-02697-7

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  • DOI: https://doi.org/10.1007/s11760-023-02697-7

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