WEATHER RECOGNITION METHOD AND DEVICE BASED ON IMAGE INFORMATION DETECTION

摘要

The embodiments of the present invention disclose a weather recognition method and device based on image information detection, which includes: obtaining an image to be detected; extracting multiple first image features of the image to be detected with respect to each preset type of weather according to a number of first preset algorithms preset correspondingly for different preset types of weather; inputting the extracted multiple first image features to a preset multi-kernel classifier, the multi-kernel classifier performing classification according to the inputted image features to identify the weather in which the image to be detected was taken; wherein the multi-kernel classifier is a classifier for the preset types of weather realized by: selecting a first preset number of image samples for the different preset types of weather in which the image was taken respectively; and for the image samples of each preset type of weather respectively, extracting the first image features of each image sample according to the first preset algorithm which corresponds to this preset type of weather; and performing machine learning for the extracted first image features according to a preset multi-kernel learning algorithm. The weather in which the image was taken can be identified by applying the solutions provided by the embodiments of the present invention.

主权项

1. A weather recognition method based on image information detection, characterized in that it includes:
obtaining an image to be detected; extracting multiple first image features of the image to be detected with respect to each preset type of weather according to a number of first preset algorithms preset correspondingly for different preset types of weather; inputting the extracted multiple first image features to a preset multi-kernel classifier, the multi-kernel classifier performing classification according to the inputted image features to identify the weather in which the image to be detected was taken; wherein the multi-kernel classifier is a classifier for the preset types of weather realized by: selecting a first preset number of image samples for the different preset types of weather in which the image was taken respectively; and for the image samples of each preset type of weather respectively, extracting the first image features of each image sample according to the first preset algorithm which corresponds to this preset type of weather; and performing machine learning for the extracted first image features according to a preset multi-kernel learning algorithm.