PROFICIENT EXPLORATION OF MALNOURISHMENT WITH MACHINE LEARNING BY CNN PROCEDURE
Prasad Dhore1, Lalit Wadhwa2, Pankaj Shinde3, Deepak Naik4, Sanjeevkumar Angadi5
1,3,4,5Assistant Professor, Department of Computer Science and Engineering
2Professor, Department of Electronics & Communication
1,3,4,5Nutan College of Engineering and Research, Talegaon Dabhade, Pune, MH, India
2Dr. D.Y Patil Institute of Technology, Pimpri, Pune, MH, India
In this paper we are expanding perception of disease finding of human body using nail image of human fingers and analyzing data from the image of elementary of nail color. The technique of disease detection is as follows: The involvement to the system is a person nail image. The system will process an image of nail and extract feature of nail which is used for disease diagnosis. Here, first training data is organized using Machine Learning from nail image of patient of specific disease. A feature extracted from input nail image is compared with training data set. In this project we found that color feature of nail image are correctly matched with training set data. Image processing is a process to convert an image into digital form and perform some operation on it & order to get an enhanced image or to extract some useful information from it. So, its execution of nail color Analysis through computer is a superior technique as compared with human eyes. This system would be cooperative for the patient, as patient need not to be present in person or if the doctor is not available for consultation purpose consequently just by receiving patient’s nail image the doctor can diagnose the symptoms and write appropriate treatment for the disease that is being analyzed.
Keywords: disease detection, nail image, image processing, malnutrition