Image Encryption Decryption Using RSA | Image Encryption Decryption Using Matlab Source Code | Final Year Major Projects

ABSTRACT

            Image security is an utmost concern in the web attacks are become more serious. The Image encryption and decryption has applications in internet communication, military communication, medical imaging, multimedia systems, telemedicine, etc. To make the data secure from various attacks the data must be encrypted before it is transmitting. Absolute protection is a difficult issue to maintain the confidentiality of images through their transmission over open channels such as internet or networks and is a major concern in the media, so image Cryptography becomes an area of attraction and interest of research in the field of information security. The project offer proposed system that provides a special kinds of image Encryption image security, Cryptography using RSA algorithm for encrypted images to extract using RSA algorithm. This approach provides high security and it will be suitable for secured transmission of images over the networks or Internet. This project is developed in matlab using RSA technique.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Mango Leaf Disease Detection Using Image Processing | Mango Plant Disease Classification Using Matlab | Final Year Major Projects

ABSTRACT

            Mango also called as The King of Fruits is one of the important fruit crops cultivated in different countries around the world. India produces about 40% of the global mango production and ranks first among the worlds mango producing countries. It is estimated that, pests and diseases destroy approximately 30 - 40% of the crop yield. The identification of plant diseases plays a vital role in taking disease control measures in order to improve the quality and quantity of crop yield. Automation of plant diseases is very much beneficial as it reduces the monitoring work in large farms. Leaves being the food source for plants, the early and accurate detection of leaf diseases is important. The mango fruit is popular because of its wide range of adaptability, high nutritional value, different variety, delicious taste and excellent flavor. The fruit contains vitamin A and vitamin C in a rich extent. The crop is prone to diseases like Powdery mildew, Anthracnose, Red Rust, etc. Disorders may also impact the plant in the absence of effective case and control measures. The farmer must consult and take professional support for the prevention / control of diseases and crop disorder. New techniques of detecting mango disease are required to promote better control to avoid this crisis. By considering this, project describes image recognition which provides cost effective and scalable disease detection technology. This project further describes new convolutional neural network models which give an opportunity for easy deployment of this technology. This project is developed in matlab using cnn in image processing.

PROJECT OUTPUT

PROECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More