%0 Journal Article %T Fusion Fourier descriptors from the EM, %+ Département STIC [Brest] (STIC) %+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC) %+ Lab-STICC_ENSTAB_CID_TOMS %+ Sciences and Technologies of Image and Telecommunications (SETIT) %A Belkhaoui, B. %A Toumi, Abdelmalek %A Khalfallah, A. %< avec comité de lecture %J International Journal of Computer and Information Technology %V 2 %N 4 %P xx %8 2013-07-01 %D 2013 %K K %K Means %K E %K M %K ISAR image %K Fisher %K Watershed s %K Fourier descriptor %K fusion %K KNN classification %Z Engineering Sciences [physics]/Electromagnetism %Z Engineering Sciences [physics]/Signal and Image processing %Z Computer Science [cs]/Signal and Image ProcessingJournal articles %X The target recognition from Radar images was a crucial step in our research. This paper presents a process a nd an adopted approach f or Automatic Target recognition using Inverse Synthetic Aperture Radar (ISAR) image . Indeed, the process adopted is composed of three steps. In the first step , we achieve the edge detection using of three techniques : Fisher, K - means and Expectation - M aximization (E - M) . Each of these techniques is combined with Watersheds (WS) algorithm to obtain the closed target shape. In order to ensure that the shape descriptors must be accurate, compact and invariant to several geometrical transformations (tran slation, rotation, scal e, etc.), we have used Fourier Descriptor computed on each obtained shape. To achieve a classification task in the last step, several techniques can be used to perform recognition tasks. We have used the nearest - neighbor classifier to retrieve a nearest kn own target for each unknow n target in the test dataset. Finally, in order to validate our proposed approach a database of ISAR images reconstructed from anechoic chamber simulations will be used . The simulation results using Fisher, E - M and K - Means method s will be presented in the last section of this paper %G English %L hal-00926818 %U https://hal.science/hal-00926818 %~ UNIV-BREST %~ INSTITUT-TELECOM %~ ENSTA-BRETAGNE %~ CNRS %~ UNIV-UBS %~ ENSTA-BRETAGNE-STIC %~ ENIB %~ LAB-STICC_ENIB %~ LAB-STICC %~ INSTITUTS-TELECOM