Abstract :
In biological sciences, herbal plants play a vital role in medicinal purpose. Identifying the leaf with unaffected leaves is more important nowadays. The leaves get affected due to many diseases like Phragmidium meuronatum, Cercospora jasmicola, Oidium tingitanium, Cephaleuros virescens. This paper focuses on the study and identification of unaffected leaves based on automated leaf recognition system. The proposed system uses image processing technique for image segmentation and feature extraction. The dataset includes 100 leaves of 10 different species. The leaves are compared with the database and the based on the threshold value the affected leaves are determined. The texture and color parameters are taken for disease authentication using image processing algorithm. Then it is fed into the real time processor Raspberry pi processor for which anywhere it can be used. The main use of Raspberry Pi is to make the system more user friendly. It uses four USB port and a real time camera which captures the image and feeds in the system. This work is more applicable in the field of agriculture and pharmaceutical industries. Debjyoti Guha | Hari Vishnu | Mr. L. Jegan Antony Marcilin | Mrs. T. Vijayashree "Real time Processor for the Authentication of Affected Herbal Medicinal Leaves Using Image Processing Techniques- Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Active Galaxy , June 2018, URL: https://www.ijtsrd.com/papers/ijtsrd14545.pdf Paper URL: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/14545/real-time-processor-for-the-authentication-of-affected-herbal-medicinal-leaves-using-image-processing-techniques--review/debjyoti-guha
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