Inception Network-Based Weather Image Classification with Pre-filtering Process

Li Wei Kang*, Tian Zheng Feng, Ru Hong Fu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


Visual data (e.g., images/videos) captured from outdoor visual devices are usually degraded by turbid media, such as haze, rain, or snow. Hence, weather conditions would usually disrupt or degrade proper functioning of vision-based applications, such as transportation systems or advanced driver assistance systems, as well as several other outdoor surveillance-based systems. To cope with these problems, removal of weather effects (or the so-called deweathering) from visual data has been critical and received much attention. Therefore, it is important to provide a preprocessing step to automatically decide the current weather condition for input visual data, and then the corresponding proper deweathering operations (e.g., removals of rain or snow) will be properly triggered accordingly. This paper presents an inception network-based weather image classification framework relying on the GoogLeNet by considering the two common weather conditions (with similar characteristics), including rain and snow, in outdoor scenes. For an input image, our method automatically classifies it into one of the two categories or none of them (e.g., sunny or others). We also evaluate the possible impact on image classification performance derived from the image preprocessing via filtering. Extensive experiments conducted on open weather image datasets with/without preprocessing are conducted to evaluate the proposed method and the feasibility has been verified.

Original languageEnglish
Title of host publicationNew Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers
EditorsChuan-Yu Chang, Chien-Chou Lin, Horng-Horng Lin
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9789811391897
Publication statusPublished - 2019
Externally publishedYes
Event23rd International Computer Symposium, ICS 2018 - Yunlin, Taiwan
Duration: 2018 Dec 202018 Dec 22

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference23rd International Computer Symposium, ICS 2018


  • Classification
  • Convolutional neural networks
  • Deep learning
  • Filtering
  • GoogLeNet
  • Inception networks
  • Preprocessing
  • Recognition
  • Weather images

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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