Moving Objects Detection & Recognition using Hybrid Canny Edge Detection Algorithm in Digital Image Processing
R. Obulakonda Reddy1, K.Reddy Madhavi2, V. Nagalakshmi3
1R. Obulakonda Reddy, Associate Professor, Department of Computer Science Engineering Institute of Aeronautical Engineering Bhopal, Madhya Prades India.
2Dr. K.Reddy Madhavi, Associate Professor, Department of Computer Science Engineering Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh India.
3V. Nagalakshmi ,Assistant Professor, Department of Computer Science Engineering Mother Theresa Institute of Engineering and Technology, Chittoor, Andhra Pradesh India.
Manuscript received on 01 July 2019 | Revised Manuscript received on 15 July 2019 | Manuscript Published on 23 August 2019 | PP: 56-60 | Volume-8 Issue-9S3 July 2019 | Retrieval Number: I30100789S319/19©BEIESP | DOI: 10.35940/ijitee.I3010.0789S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Recognition and detection of an object in the watched scenes is a characteristic organic capacity. Animals and human being play out this easily in day by day life to move without crashes, to discover sustenance, dodge dangers, etc. Be that as it may, comparable PC techniques and calculations for scene examination are not all that direct, in spite of their exceptional advancement. Object detection is the process in which finding or recognizing cases of articles (for instance faces, mutts or structures) in computerized pictures or recordings. This is the fundamental task in computer. For detecting the instance of an object and to pictures having a place with an article classification object detection method usually used learning algorithm and extracted features. This paper proposed a method for moving object detection and vehicle detection.
Keywords: Detection, Digital Image, Object, Recognition.
Scope of the Article: Image Processing and Pattern Recognition