A Dynamic Image Matching Model and Architecture for Smart Devices

The aim of this research is on developing a dynamic image matching model (DIMM) for smart devices. People with no knowledge on searching keywords can see the information and make good use of it in their daily life. Although existing search engines (Google, Yahoo etc.) have this systems, but it is necessary to get the information of any objects from anywhere on any platform. To fulfill this requirement a unique model and architecture is proposed for ending users thirsts in both offline and online. The proposed model has four planes. The users are sited in the top plane. In the second plane, object attributes are checked automatically by the system administrator. The core system is in the third plane which is responsible for extended feature extraction, object matching and object categorization etc. Finally, the core system retrieves the information from the fourth plane where object information stored in different databases. The output of DIMM is: a user can enjoy the object information from anywhere, such as, home, office, train station, Himalaya, etc. Any platform indicates that the user can enjoy the image information from smart phones, PDA, palmtop, home appliances, personal computer, etc. that means, the system is not limited to hardware and software. Open CV 2.2 is used for both the Android and iPhone for the DIMM experiment.