TY - JFULL AU - R. A. Salam and M.A. Rodrigues PY - 2008/2/ TI - Mining Image Features in an Automatic Two-Dimensional Shape Recognition System T2 - International Journal of Computer and Information Engineering SP - 242 EP - 249 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/688 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 13, 2008 N2 - The number of features required to represent an image can be very huge. Using all available features to recognize objects can suffer from curse dimensionality. Feature selection and extraction is the pre-processing step of image mining. Main issues in analyzing images is the effective identification of features and another one is extracting them. The mining problem that has been focused is the grouping of features for different shapes. Experiments have been conducted by using shape outline as the features. Shape outline readings are put through normalization and dimensionality reduction process using an eigenvector based method to produce a new set of readings. After this pre-processing step data will be grouped through their shapes. Through statistical analysis, these readings together with peak measures a robust classification and recognition process is achieved. Tests showed that the suggested methods are able to automatically recognize objects through their shapes. Finally, experiments also demonstrate the system invariance to rotation, translation, scale, reflection and to a small degree of distortion. ER -