This paper describes an automatic fault location technique for permanent faults in underground LV distribution networks (ULVDNs). It uses signals from an existing time domain reflectometry (TDR) instrument. It pre-processes TDR signals to eliminate reflections due to single-phase tee-offs, and to locate 3-phase open or short circuit faults and also uses adaptive filtering to compare the TDR signals to locate faults. In essence, the procedure minimizes the interpretation skill required from a user of a typical TDR based fault location instrument. The relative performance of the system is demonstrated using real field data

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The pupil detection system plays a vital role in ophthalmology diagnosis equipments because pupil has a center place of human eye to locate the exact position. To identify the exact human eye pupil region in near infrared (NIR) images, this work proposes the Center of gravity method and its real time FPGA hardware implementation. The proposed work involves global threshold method to segment the pupil region from human eye and the bright spot suppression process removes the light reflections on the pupil due to the IR (Infra red) rays then the morphology dilation process removes unnecessary black pixels other than pupil region on the image. Finally, center of gravity (COG) method provides the exact pupil center coordinate and radius of the human eye. CASIA IRIS V4 and UBIRIS iris database images used in this work and achieved 90-95% of recognition rate.

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