Cloud – based object recognition: A system proposal Daniel LORENČÍK 1 , Peter SINČÁK 2 Abstract In this chapter, we will present a proposal for the cloud – based object recognition system. The system will extract the local features from the image and classify the object on the image using Membership Function ARTMAP (MF ARTMAP) or Gaussian Markov Random Field model. The feature extraction will be based on SIFT, SURF and ORB methods. Whole system will be built on the cloud architecture, to be readily available for the needs of the new emerging tech- nological field of cloud robotics. Besides the system proposal, we specified re- search and technical goals for the following research. 1 Introduction Since the history of computers and computing began roughly 70 years ago, we have seen the large scale computers replaced by affordable personal computers. In the last years, we are witnesses to another notion – the personal computers shrank in size to tablets, netbooks and even smartphones, and the heavy computational and storage tasks are offloaded to the cloud. Also, the applications available on the cloud have high impact on the productivity as they allow for easy implementation on sharing data between several users, thereby promoting real-time collaboration and aggregation of crowd knowledge, example being the Google Apps suite [1] or Microsoft Office 365 [2]. With this knowledge in mind, it is possible to envision the similar system of application which will be available for use by robots. The obvious benefit is the possibility of creating small robots with greater longevity of battery life since the heavy computation is done elsewhere. These robots will not have to be highly so- phisticated. Therefore, they can be cheap or can be created from available re- sources like smartphones combined with the wheeled chassis. More than that, the robots can benefit from the sharing of knowledge. This idea was presented by pro- 1 Department of Cybernetics and Artificial Intelligence, Technical University of Košice daniel.lorencik@tuke.sk 2 Department of Cybernetics and Artificial Intelligence, Technical University of Košice peter.sincak@tuke.sk