Determining clean or dirty captured images

A system for determining whether an image captured by a capturing device is clean or dirty, the system comprising:

• a receptor module to receive the image captured by the image capturing device;
• a splitter module to split the received image into a plurality of image portions according to a predefined-splitting-criteria;
• a filter module to perform, for each of at least some of the image portions, a Laplacian filter of the image portion to produce a feature vector including Laplacian filter features of the image portion;
• a provider module to provide each of at least some of the produced feature vectors to a first machine learning module that has been trained to produce a clean/dirty indicator depending on corresponding feature vector, the clean/dirty indicator including a probabilistic value of cleanness or dirtiness of corresponding image portion;
• and
• a state-determiner module to determine whether the image is clean or dirty depending on the clean/dirty indicators produced by the first machine learning module.

A method comprising:

• receiving a captured image;
• splitting the captured image into a plurality of image portions according to a predefined-splitting-criteria;
• performing, for each of at least some of the plurality of image portions, a Laplacian filter to produce a feature vector including Laplacian filter features for each of the at least some of the plurality of image portions;
• providing each of at least some of the produced feature vectors to a first machine learning module that produces a clean/dirty indicator based on a corresponding feature vector, the clean/dirty indicator including a probabilistic value of cleanness or dirtiness of a corresponding image portion;
• and
• determining whether the image is clean or dirty based on clean/dirty indicators.