Detection and Retrieval of Human Falls on Furniture using Hybrid Method
Mettu Kavya Reddy1, K. Sripal Reddy2, M.Narayana3
1Mettu Kavya Reddy*, Digital Electronics and Communication, Vardhaman College of Engineering, Hyderabad, India.
2K. Sripal Reddy, Assistant professor, Electronics and Communication, Vardhaman College of Engineering, Hyderabad, India.
3Dr. M. Narayana, professor, Electronics and Communication, Vardhaman College of Engineering, Hyderabad, India.
Manuscript received on July 11, 2019. | Revised Manuscript received on August 21, 2019. | Manuscript published on August 30, 2019. | PP: 4842-4849 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9119088619/2019©BEIESP | DOI: 10.35940/ijeat.F9119.088619
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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: Automatic detection of human falls is very important to detect accidental falls at Medical places , and at places where elderly and vulnerable people living alone at home. Many methods have been proposed to detect human falls using various approaches, but cannot give accurate results in complex environments. This paper proposes a new hybrid method which detects falls and then retrieve relevant images. The proposed algorithm first calculates the features of hybrid methods and retrieve the similar images from the database using various methods. the proposed method achieves up to 97.5% precision and recall of 73%.
Keywords: Scene Analysis, GLCM, Wavelet Transform, Histogram, Human fall detection.