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Mobile phones provide important services like GPS, short-range wireless communications using infrared or Bluetooth, business applications, mobile banking etc. Mobile hard-ware add--ons are also popular like, handheld keyboard with mobile phone, mobile with handheld miniature microscope (phonoscope) and others. Imaging is one of the most important features of mobile technology. Magnified images are providing in depth recognition capabilities of object. Mobile based microscope is used for Geology, Biological, Medicine, Horticulture and others areas. Objective of this paper is to present a method for rock identification using mobile based microscope camera imaging of surface parameter. Rock surface parameters are color, grain, texture. The development in the area of mobile application has opened new challenges in mobile image processing. In this paper we demonstrate a method that adopts microscope optics into mobile camera optics and developed java based (J2ME) mobile application for recognizing rock type. This consists of feature extraction algorithm using wavelet based data compression and neural network based feature classification. Rock surface parameters used in this work is grain. The signature extracted from grain parameter is used to identify the rock type.