Vitamin Deficiency Detection Using Image Processing and Neural Network.
Objective
The main objective of the project is to detect the deficiency in the organs of the human bod by considering the texture.
Abstract
A wide spectrum of vitamin deficiencies can show one or more visually distinguishable symptoms and indications that appear in multiple locations in the human body. The application provides individuals with the capability to diagnose their possible vitamin deficiencies without the need to provide blood samples through the analysis of photos taken of their eyes, lips, tongue, and nails. This process is implemented using the deep learning based CNN algorithm. Here we have considered the dataset of eyes, lips, tongue and lips. Once after the consideration of dataset, the pre-processing is performed and then CNN algorithm is used to train the data. Once after the training, model is saved and the testing is performed using the OpenCv.
Keywords: Vitamin deficiency, deep learning, CNN, OpenCV
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
H/W Specifications:
- Processor:
I3/Intel Processor
- RAM: 8GB (min)
- Hard Disk: 128 GB
S/W Specifications:
- Operating System: Windows 10
- Server-side Script: Python 3.6
- IDE: PyCharm
- Libraries Used : Numpy, IO, OS, Flask, keras, OpenCV
Learning Outcomes
Practical exposure to
· Hardware and software tools
· Solution providing for real time problems
· Working with team/individual
· Work on creative ideas
· Testing techniques
· Error correction mechanisms
· What type of technology versions is used?
· Working of Tensor Flow
· Implementation of Deep Learning techniques
· Working of CNN algorithm
· Working of Transfer Learning methods
· Building of model creations
· Scope of project
· Applications of the project
· About Python language
· About Deep Learning Frameworks
· Use of Data Science
Related Projects
Paper Publishing
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