@inproceedings{5dc26bc68288451291c8c297ddf95519,
title = "A parallel distributed processing algorithm for image feature extraction",
abstract = "We present a new parallel algorithm for image feature extraction. which uses a distance function based on the LZ-complexity of the string representation of the two images. An input image is represented by a feature vector whose components are the distance values between its parts (sub-images) and a set of prototypes. The algorithm is highly scalable and computes these values in parallel. It is implemented on a massively parallel graphics processing unit (GPU) with several thousands of cores which yields a three order of magnitude reduction in time for processing the images. Given a corpus of input images the algorithm produces labeled cases that can be used by any supervised or unsupervised learning algorithm to learn image classification or image clustering. A main advantage is the lack of need for any image processing or image analysis; the user only once defines image-features through a simple basic process of choosing a few small images that serve as prototypes. Results for several image classification problems are presented.",
author = "Alexander Belousov and Joel Ratsaby",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 14th International Symposium on Intelligent Data Analysis, IDA 2015 ; Conference date: 22-10-2015 Through 24-10-2015",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-24465-5_6",
language = "English",
isbn = "9783319244648",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "61--71",
editor = "{De Bie}, Tijl and {van Leeuwen}, Matthijs and Elisa Fromont",
booktitle = "Advances in Intelligent Data Analysis XIV - 14th International Symposium, IDA 2015, Proceedings",
address = "Germany",
}