Automatic Fish Cutting and Cleaning Machine using Digital Image Processing
M. Bhuvaneswari1, R. Emmanuel Gospel Raj2, T. Vignesh3 

1M.Bhuvaneswari, Department of Mechatronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu.
2R.Emmanuel Gospel Raj, Department of Mechatronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu.
3T.Vignesh, Department of Mechatronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu.

Manuscript received on 04 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 612-615 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1635078219/19©BEIESP | DOI: 10.35940/ijrte.B1635.078219
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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: There are many varieties of fishes available in the market and the consumers are increasing day by day. This paper is mainly concentrated on automatic cleaning and cutting of fish. There is huge demand for fish cutting and cleaning machine in the market for easy use. Time and labor can be effectively managed if this type of machine is implemented in the fish market. This paper introduces the concept of Digital image processing technology to identify the various types of fishes and their sizes. Special convey rollers mechanism need to be designed and developed for handling different types of fishes. Technology will ensuring hygiene, quality and waste disposal. The following are the objectives of this paper design and implement Automatic Fish Cutting and Cleaning Machine. The shape, size of fish is analyzed using Digital Image Processing techniques. This will improve the living standard of rural women who sells different variety of fishes in the market, which empowers women in the society.
Index Terms: Fish Cutting and Cleaning, Digital Image Processing, Conveyers.

Scope of the Article: Machine Learning