Matlab Code for Plant Disease Detection using Neural Network

ABSTRACT

            The detection and classification of plant diseases are the crucial factors in plant production and the reduction of losses in crop yield. This paper proposes an approach for leaf disease detection and classification on plants using image processing. The algorithm presented has three basic steps: Image Pre-processing and analysis, Feature Extraction and Recognition of plant disease. The plant disease diagnosis is restricted by person’s visual capabilities as it is microscopic in nature. Due to optical nature of plant monitoring task, computer visualization methods are adopted in plant disease recognition. The aim is to detect the symptoms of the disease occurred in leaves in an accurate way. Once the captured image is pre-processed, the various properties of the plant leaf such as intensity, color and size are extracted and sent to with Neural Network for classification. 

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Mr. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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Image Steganography Data Hiding in Cover Image Full Source Code

ABSTRACT

            Today, digital communication has become an integral part of everyday life. Many applications are based on the Internet and communications must be made in secret. This is especially important when confidential information needs to be exchanged. As a result, the security of information transmitted over public channels is a fundamental problem, and as a result, the confidentiality and integrity of the data is essential to protect against unauthorized access and use. This caused the information concealment area to become unstable. Encryption and steganography are two of the most common methods you can use to ensure safety. With encryption, the data is converted to another form of gibberish and the encrypted data is transmitted. In Steganography, the image and text is transferred to the image, which is embedded in the image without affecting the quality of the image.This project suggests a new way to embed data into images with secret key.

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Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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Steganography using RSA Algorithm - Encryption & Decryption using RSA Source Code

ABSTRACT

            Steganography is a method of hiding secret messages in a cover object while communication takes place between sender and receiver. Security of confidential information has always been a major issue from the past times to the present time. It has always been the interested topic for researchers to develop secure techniques to send data without revealing it to anyone other than the receiver. Therefore from time to time researchers have developed many techniques to fulfill secure transfer of data and steganography is one of them. In this project we have proposed a new technique of image steganography using RSA algorithm for providing more security to data as well as our data hiding method. The proposed technique frist generate a pattern for hiding data bits into pixel values of the cover image. This technique makes sure that the message has been encrypted before hiding it into a cover image. If in any case the cipher text got revealed from the cover image, the intermediate person other than receiver can't access the message as it is in encrypted form.

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Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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Python Project on Age and Gender Recognition using CNN Convolutional Neural Network

ABSTRACT

         Automatic age and gender classification has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. Nevertheless, performance of existing methods on real-world images is still significantly lacking, especially when compared to the tremendous leaps in performance recently reported for the related task of face recognition. In this project we show that by learning representations through the use of deep-convolutional neural networks (CNN), a significant increase in performance can be obtained on these tasks. To this end, we propose a simple convolutional net architecture that can be used even when the amount of learning data is limited. We evaluate our method on the recent Audience benchmark for age and gender estimation and show it to dramatically outperform current state-of-the-art methods.

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Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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