Rice Leaf Disease Detection Using Image Processing | Rice Plant Disease Classification Using Python Project with Source Code | Final Year Major Projects Code

ABSTRACT

                Agriculture plays an important role in the economic growth of every country and so it is necessary to ensure its development. The spread of various diseases in rice plants has increased in recent years. There is a variety of plant pathogens such as viral, bacterial, fungal and these can damage different plant parts above and below the ground. Agriculture is the primary source of livelihood for about more than 50% of the Indian population and rice is one of the major food grains of India. It is observed that rice plant diseases are the major contributors to reduce the production & quality of food. Identification of such diseases may improve the production quality. This project gives an idea about deep learning algorithm which is used to detect deadly diseases in rice plants. Much research has been done to automate the rice plant disease detection process using images of the leaf. This project is developed in python with accuracy of up to 99%.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

Read More

Image Steganography Using DWT Algorithm | Image Steganography Using Python Project With Source Code | Hiding Text Message In Image Using DWT | Final Year Project

ABSTRACT

            Steganography is the science and art of secret communication between two sides that attempt to hide the content of the message. It is the science of embedding information into the cover image without causing a loss in the cover image after embedding. Steganography is the art and technology of writing hidden messages in such a manner that no person, apart from the sender and supposed recipient, suspects the lifestyles of the message. It is gaining huge attention these days as it does now not attract attention to its information's existence. In this project the secret message is embedded using DWT technique is applied. Moreover, Discrete Wavelet Transform (DWT) is used to transform the image into the frequency domain.  DWT algorithm is implemented in frequency domain in which the stego-image is transformed from spatial domain to the frequency domain and the payload bits are inserted into the frequency components of the cover image. This project is developed in python.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Tuberculosis Detection Using Deep Learning | Tuberculosis Classification Using Python Projects With Source Code | Final Year Major Projects

ABSTRACT

          Lung problems encompass an array of lung disorders, including asthma, TB, lung disease, and numerous other respiratory disorders. For many years, tuberculosis has been a significant public health issue. TB is usually diagnosed with chest X-rays, which are essential tools for screening and detecting the disease. In spite of this, accurate diagnosis of TB using chest X-rays is challenging due to the complexity of the disease and the variation in how it appears on images. In medical image analysis, including in TB recognition in chest, deep learning techniques have been widely used. This project is developed in python using deep learning approach. 

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

Read More

Sugarcane Leaf Disease Detection Using Machine Learning | Sugarcane Plant Disease Classification Using Matlab Project With Source Code | Final Year Major Project

ABSTRACT

                    Now-a-days wheat plants are getting infected by different types of diseases very rapidly. It is must to come up with new system to single out diseases. It is must to design and implement such a system that can easily find out the diseases infected by plants. In India many crops are cultivated, out of which wheat being one of the most important food grain that this country cultivates and exports. Thus it can be seen that wheat forms a major part of the Indian agricultural system and India’s economy. Hence, maintenance of the steady production of above stated crop is very important. The main idea of this project is to provide a system for detecting sugarcane leaf diseases. The given system will find the disease on leaf image of a sugarcane plant through image processing this project is develop in matlab. Former algorithms are used for extracting vital information from the leaf and the latter is used for detecting the disease that it is infected with. This Project is developed in matlab using machine learning.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Image Encryption And Decryption Using DNA Algorithm | DNA Based Image Encryption Decryption Using Matlab Projects With Source Code | Final Year Projects

ABSTRACT

      The development of a new image encryption algorithm using real structures of deoxyribonucleic acid (DNA) molecules is considered. In the proposed algorithm, the encryption process is performed by confusing and rearranging the pixels of the image based on the coordinates of the chaotic points obtained by the chaos game of DNA symbols, the sequence of DNA symbols, and the encoding rule. We propose a new image encryption algorithm based on DNA sequences combined with chaotic maps. This algorithm has innovations it diffuses the pixels by transforming the nucleotides into corresponding base pairs a random number of times. For any size of the original grayscale image, the rows and columns are fist exchanged by the arrays generated each pixel that has been confused is encoded into four nucleotides according to the DNA coding each nucleotide is transformed into the corresponding base pair a random number of time(s) by a series of iterative computations. This project is developed in matlab.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

Read More

Lumpy Disease Detection Using Image Processing | Lumpy Skin Classification Using Matlab Project Source Code | Final Year Major Project

ABSTRACT

          Animal illness is now a widespread problem. sickness identification is essential because there are various sorts of sickness in creatures, and the opinion will be delivered in a timely manner. Cows with the Neethling infection develop lumpy skin complaints. The affection of these illnesses causes lasting harm to the cattle's skin. Reduced milk production, gravidity, poor growth, revocation, and, in severe cases, mortality, are the most common effects of the illness. We developed a deep learning-based architecture that can predict or detect disease. To discover the pathogen that causes lumpy skin problem, it is crucial to employ a deep literacy system. The virus (LSDV) that causes lumpy skin disease can infect cattle. Ticks and other animals that feed on blood, such as flies, mosquitoes, and ticks, spread it. Animals who have never been exposed to the disease may develop nodes on their skin, a fever, and even pass away as a result of it. Two methods of control are vaccinations and rewarding afflicted creatures. The purpose of this study was to evaluate how well some deep learning algorithms could understand the context of an infection causing a Lumpy Skin complaint. This project is developed in matlab using image processing.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +917276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Currency Recognition Using Deep Learning CNN | Currency Classification Using Python Project With Source Code | Final Year Major Project

ABSTRACT

             The Reserve Bank is the one which issue bank notes in India. Reserve Bank, changes the design of bank notes from time to time. The appearance of the currency is part of this development and it is affected directly, where there is exploited in incorrect form by copying the currency in a manner similar to the reality. Therefore, it became necessary to implement a proposal for being a suitable as solution not inconsistent with the different cultures, time and place. This clear through add the watermarks inside currency, which is difficult to be copied. At the same time, this watermarks may be visible to the naked eye so can easily inferred or it is invisible. However the high resolution imaging devices can copy these additions. In this research, we have proposed a system to distinguish the currencies by the program that working a submission inferred to the watermark by feature extraction determined the type of currency. In addition to, it determined category of the currency. Benefit of it, is reducing as much as possible the spread of counterfeit currency and this system can be used by any user wants to make sure of the currency. This project is developed in python using deep learning cnn.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +917276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Banana Leaf Disease Detection Using CNN | Banana Plant Disease Classification Using Matlab Project With Source Code | Final Year Major Project

ABSTRACT

             Disease diagnosis and classification in banana crop using image processing technique is an interesting and useful application for farmers to identify, analyze and manage plant pathogens within fields as effectively and automatically at minimum cost. Major banana diseases express their symptoms on leaf area in their earlier stage of infection. These disease can be analyzed and classified automatically through computer vision and machine vision systems that use image processing techniques for information interpretation. This project shows various disease identified on banana plant leaf using cnn convolutional neural network. This project is develop in matlab.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

Read More

Visible Image Watermarking Using DWT Technique | Visible Image Watermarking Using Python Project With Source Code | Final Year Major Projects

ABSTRACT

           Digital watermarking is a technology for embedding various types of information in digital content. In general, information for protecting copyrights and proving the validity of data is embedded as a watermark. A digital watermark is a digital signal or pattern inserted into digital content. The digital content could be a still image, an audio clip, a video clip, a text document, or some form of digital data that the creator or owner would like to protect. The main purpose of the watermark is to identify who the owner of the digital data is, but it can also identify the intended recipient. The Image watermarking is most popular method for copyright protection by discrete Wavelet Transform which performs two level decomposition of original cover image and watermark image is embedded in lowest level sub band of cover image. Inverse Discrete Wavelet Transform is used to recover original image from watermarked image. This project is developed in python.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Traffic Sign Recognition Using Deep Learning | Traffic Sign Classification Using Python Project With Source Code | Final Year Major Project Code

ABSTRACT

               Traffic sign recognition is an important but challenging task, especially for automated driving and driver assistance. Its accuracy depends on two aspects: feature exactor and classifier. Current popular algorithms mainly use deep learning cnn to execute feature extraction and classification. Such methods could achieve impressive results but usually on the basis of an extremely huge and complex network. What’s more, since the fully-connected layers in cnn form a classical neural network classifier, which is trained by conventional gradient descent-based implementations, the generalization ability is limited. The performance could be further improved if other favorable classifiers are used in python with accuracy of upto 98 %.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Skin Disease Detection Using Deep Learning | Skin Disease Classification Using Matlab Project With Source Code | Final Year Major Projects

ABSTRACT

          Skin diseases are more common than other diseases. Skin diseases may be caused by fungal infection, bacteria, allergy, or viruses, etc. A skin disease may change texture or color of the skin. In general, skin diseases are chronic, infectious and sometimes may develop into skin cancer. The advancement of lasers and Photonics based medical technology has made it possible to diagnose the skin diseases much more quickly and accurately. But the cost of such diagnosis is still limited and very expensive. So, image processing techniques help to build automated screening system for dermatology at an initial stage. The extraction of features plays a key role in helping to classify skin diseases. Computer vision has a role in the detection of skin diseases in a variety of techniques. Due to deserts and hot weather, skin diseases are common in various country. We proposed an image processing-based method to detect skin diseases. This method takes the digital image of disease effect skin area, then use image analysis to identify the type of skin disease. This project is developed in matlab using deep learning techniques.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +917276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Skin Cancer Classification Using CNN Convolutional Neural Network | Skin Cancer Detection Using Python Project With Source Code | IEEE Project with Source Code

ABSTRACT

                Many of the skin diseases are very dangerous, particularly if not treated at an early stage. Skin diseases are becoming common because of the increasing pollution. Skin diseases tend to pass from one person to another. Human habits tend to assume that some Melanoma Skin Cancer are not serious problems. Sometimes, most of the people try to treat these infections of the skin using their own method. However, if these treatments are not suitable for that particular skin problem then it would make it worse. And also sometimes they may not be aware of the dangerous of their Melanoma Skin Cancer, for instance skin cancers. With advance of medical imaging technologies, the acquired data information is getting so rich toward beyond the human’s capability of visual recognition and efficient use for clinical assessment. In this project we propose a diagnosis system which will enable users to detect and recognize skin diseases with the help of image processing and provide the user advises or treatments based on the results obtained in a shorter time period than the existing methods. In this project, we will be constructing a diagnosis system based on the techniques of Image Processing. We will be making use of Python to perform the pre-processing and processing of the skin images of the users. This processing will be conducted on the different skin patterns and will be analyzed to obtain the results from which we can identify which skin disease the user is suffering from. This data will help in early detection of the skin diseases and in providing their cure. Through this we will be finding a cost effective and feasible test method for the detection of skin disorders. The results obtained will be classified according to the given prototype and diagnosis accuracy assessment will be performed to provide users with efficient and fast results.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Paddy Leaf Disease Detection Using Image Processing | Paddy Plant Disease Classification Using Matlab Project With Source Code

ABSTRACT

           Agriculture is the main backbone for most of the developing/developed countries; agriculture production itself is the main feed for ever growing populations and it is the major source of income for the rural people/farmers especially in India. In India farmers are called “the backbone of India”. The main aim of the proposed system is to detect, classify the diseases in paddy leafs. Paddy leaf diseases detection done using image processing and cnn techniques. The proposed system has been experimentally tested for our own dataset and results achieved are encouraging. The spread of plant pests and diseases has increased dramatically in recent years. Globalization, trade and climate change, as well as reduced resilience in production systems due to decades of agricultural intensification, have all played a part. Plant pathogens can be fungal, bacterial, viral or nematodes and can damage plant parts above or below the ground. This project is developed in matlab.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Vegetable Leaf Classification Using Deep Learning Matlab Project | Vegetable Plant Recognition Using Matlab Project With Source Code

ABSTRACT

             Leaf Recognition is now emerging for research purposes. Leaf recognition technology plays an important role in plant classification and its key issue lies in whether selected features are stable and have good ability to discriminate different kinds of leaves. It is well known that the correct way to extract plant features involves plant recognition based on leaf images. In Agriculture, vegetables plants have become an important source of energy and source of living for farmers. Correctly identifying a vegetable leaf allows farmers to differentiate between vegetables as well as a vegetable seedling and weed in the garden. With so many varieties of leafy greens coming from our local farmers each week, it can be difficult to figure out vegetable it belongs to. Though these leaves may appear similar at a glance, they are actually quite unique in terms of Shape, Texture and Color. And with the increasing use of innovative computer technology, digitalized ways have become a possibility for plant identification. The proposed system will solve the problem of determining the vegetables just through the photograph of their leaves. In particular, identification process is carried out by gathering leaves detached from the plants, treated and stained prior to the imaging. Recognition of Vegetable Leaf using Matlab project, is to create an Informative Vegetable’s Leaf Recognition using Matlab to help the farmers, botanist and Agricultural Researchers in identifying a vegetable and its common details in a convenient and reliable way. The output parameters are used to compute well documented metrics for the statistical and shape. Base on the study, the following conclusion are drawn: The system can extract various parameters from the leaf’s image that will be used in identifying Vegetable`s from the extracted leaf parameters, the system provides the statistical analysis and general information of the identified leaf. This project is developed in matlab.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Lumpy Disease Detection Using Image Processing | Lumpy Skin Classification Using Python Project Source Code | Final Year Project

ABSTRACT

          Animal illness is now a widespread problem. sickness identification is essential because there are various sorts of sickness in creatures, and the opinion will be delivered in a timely manner. Cows with the Neethling infection develop lumpy skin complaints. The affection of these illnesses causes lasting harm to the cattle's skin. Reduced milk production, gravidity, poor growth, revocation, and, in severe cases, mortality, are the most common effects of the illness. We developed a deep learning-based architecture that can predict or detect disease. To discover the pathogen that causes lumpy skin problem, it is crucial to employ a deep literacy system. The virus (LSDV) that causes lumpy skin disease can infect cattle. Ticks and other animals that feed on blood, such as flies, mosquitoes, and ticks, spread it. Animals who have never been exposed to the disease may develop nodes on their skin, a fever, and even pass away as a result of it. Two methods of control are vaccinations and rewarding afflicted creatures. The purpose of this study was to evaluate how well some deep learning algorithms could understand the context of an infection causing a Lumpy Skin complaint. This project is developed in python using image processing.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +917276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More

Foot Ulcer Detection Using Image Processing Using Matlab | Foot Ulcer Classification Using Matlab Project With Source Code

ABSTRACT

         Now a days, diabetic patient are more prone to have foot ulcer. Diabetes affects the foot generally by two ways, such as breaking of nerves and weakening of blood vessels. Strange increase of glucose in the blood results in nerve injury, termed as diabetic neuropathy. Lack of sensation and hardening of the foot may indicate nerve injury. Due to this, diabetic patients would not sense a small wound or an inflammation on foot. Lack of sensation in the foot may cause abnormal walking and standing. Flattered arches fractures and non-healing blisters may occur due to improper balance of foot. Diabetes also has an effect on blood vessels. Thin blood vessels carry a lesser amount of blood to the foot. Oxygen is conceded to the blood cell. When the blood vessels are tapering, less blood and oxygen reaches the foot. This can delay wound healing. Insufficient blood will not carry sufficient oxygen and nutrient to the foot for healing and fight against infection. Gangrene may also affect the diabetic patient due to lack of blood supply. Treatment may require an amputation of the foot. The infected part of the foot was removed surgically. Initial finding, care and treatment can avoided the need of amputation. Symptoms such as redness, swelling, and increase temperature are the indication of foot ulcer. In this project an image processing technique is proposed to identify weather ulcer is healing or not. This project is developed in matlab.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +917276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

Read More