Unsupervised Image Sorting
The goal of this work is to approximately solve the problem of unsupervised image sorting that is considered as a kind of content-based image clustering. The content-based image sorting is the creation of a route that passes through all the images once, in such an order that the next one from the previous image has similar content.
In the end, an image ordering (e.g. slideshow) is automatically produced, so that the images with similar content should be close to each other. This problem resembles the problem known in the literature as ‘travelling salesman problem’ (TSP). Two classes of methods (the nearest-neighbour and genetic methods) has been proposed that have also been applied on the TSP problem.
We will appreciate if you cite our paper [1] in your work:
[1] Markaki, S., Panagiotakis, C., & Lasthiotaki, D. (2019). Image sorting via a reduction in travelling salesman problem. IET Image Processing.
The datasets can be downloaded from https://sites.google.com/site/costaspanagiotakis/research/unsupervised-image-sorting
Cite As
Costas Panagiotakis (2024). Unsupervised Image Sorting (https://www.mathworks.com/matlabcentral/fileexchange/73660-unsupervised-image-sorting), MATLAB Central File Exchange. Retrieved .
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