Matlab code for Fish Disease Detection using Neural Network

ABSTRACT
             There is a lot of expert knowledge in fish disease diagnostic process. Aimed at the drawbacks of expert diagnosis such as low level of intelligence and poor practicality, a new structure of fish disease diagnostic expert system based on neural networks is proposed. The diagnosis system uses the old cases of fish disease to train the neural network, and the disease diagnosis is achieved through the trained neural network. This method can realise the diagnosis of fish disease timely and rapidly, and provide a new effective method to the development of fish disease diagnosis system. 

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Mr. Roshan P. Helonde
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Matlab Code for Image Steganography Using DCT Algorithm

ABSTRACT
            Steganography is one of the methods of secret communication that hides the existence of message so that a viewer cannot detect the transmission of message and hencecannot try to decrypt it. It is the process of embedding secret data in the cover image without significant changes to the cover image. These algorithms keep the messages from stealing, destroying from unintended users on the internet and hence provide security. The proposed technique use Discrete Cosine Transform (DCT). The proposed method calculates each DC coefficient and replace with each bit of secret message. The proposed embedding method using DCT.

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Mr. Roshan P. Helonde
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WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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Lung Cancer Detection using Image Processing Matlab Source Code

ABSTRACT
             Lung cancer prevalence is one of the highest of cancers. One of the first steps in lung cancer diagnosis is sampling of lung tissues or biopsy. These tissue samples are then microscopically analyzed. This procedure is taken once imaging tests indicate the presence of cancer cells in the chest. Lung cancer diagnosis using lung images. One of them is that doctor still relies on subjective visual observation. A medical specialist must do thorough observation and accurate analysis in detecting lung cancer in patients. Hence, there is need for a system that is capable for detecting lung cancer automatically from microscopic images of biopsy. This method will improve the accuracy and efficiency for lung cancer detection. The aim of this research is to design a lung cancer detection system based on analysis of microscopic image of biopsy using digital image processing. Microscopic images of biopsy are feature extracted and classified.

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Mr. Roshan P. Helonde
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Email: roshanphelonde@rediffmail.com
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Matlab Code for Image Encryption Decryption Using Arnold Transform for Image scrambling

ABSTRACT
           Digital image scrambling can make an image into a completely different meaningless image during transformation, and during hiding information of the digital image, which also known as information disguise. Image scrambling technology depends on data hiding technology which provides non-password security algorithm for information hiding. Data hiding technology led to a revolution in the warfare of network information, because it brought a series of new combat algorithms, and a lot of countries pay a lot of attentions on this area. Network information warfare is an important part of information warfare, and its core idea is to use public network for confidential data transmission. The image after scrambling encryption algorithms is chaotic, so attacker cannot decipher it.

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Mr. Roshan P. Helonde
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Matlab Code Corn Leaf Disease Detection Using Image Processing

ABSTRACT
            Plant leaf diseases can affect plant leaves to a certain extent that the plants can collapse and die completely. These diseases may drastically decrease the supply of vegetables and fruits to the market, and result in a low agricultural economy. In the literature, different laboratory methods of plant leaf disease detection have been used. These methods were time consuming and could not cover large areas for the detection of leaf diseases. A novel way of training and methodology was used to expedite a quick and easy implementation of the system in practice. The developed model was able to recognise different types of Corn leaf diseases out of healthy leaves, Corn Leaf Blight (Exserohilum), Common Rust (Puccinia Sorghi) and Corn Leaf Spot (Cercospora) diseases were chosen for this study as they affect most parts of Corn Plant.

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Mr. Roshan P. Helonde
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Matlab Code for Fingerprint Recognition using Image Processing

ABSTRACT
        Recently, monitoring and security have become an essential and important affair because the number of counterfeiters and hacker are increased for the conventional methods like Personal Identification Number (PIN) and passwords. The traditional methods suffer from some type of contraventions and breaches for example the unauthorized user can arrive to important data in a dedicated system to delete, change, or even steal it. For averting whole these concerns; the modern community directs to more credibility methods recently utilize the biometric-technologies. Biometrics provides more secure way of person authentication, they are difficult to be stolen and replicated. Biometrics method can be depicted as an automate technique to recognize person automatically based on his or her behavioral and/or physiological features. This technology has possessed a big amount of concern and care for security in almost all aspects of our daily life since person cannot forget or lose their physiological features in the way that they might lose password or an identity card. Biometric technologies have been developed for automatic recognizing of human identity depending on person special biological features, such as face, Iris, speech and fingerprint. The online security of authentication systems is not only a substitution of secret codes and passwords, but it is also related to securing and monitoring the system in different level of potential applications. This project was analyzed and evaluation Uni-modal biometric system based on fingerprint identification system. 

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Mr. Roshan P. Helonde
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Matlab Code for Iris Recognition Using Image Processing Source Code

ABSTRACT
             This project presents an iris coding method for effective recognition of an individual. The recognition is performed based on a mathematical and computational method. It consists of calculating the differences coefficients of overlapped angular patches from the normalized iris image for the purpose of feature extraction. Iris recognition belongs to the biometric identification. Biometric identification is a technology that is used for the identification an individual based on ones physiological or behavioral characteristics. Iris is the strongest physiological feature for the recognition process because it offers most accurate and reliable results. Iris recognition process mainly involves three stages namely, iris image preprocessing, feature extraction and template matching. In the pre-processing step, iris localization algorithm is used to locate the inner and outer boundaries of the iris. Detected iris region is then normalized to a fixed size rectangular block. In the feature extraction step, texture analysis method is used to extract significant features from the normalized iris image.


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Mr. Roshan P. Helonde
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Email: roshanphelonde@rediffmail.com
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PHP Website Project Source Code Nation Level Technical Event

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Mr. Roshan P. Helonde
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Email: roshanphelonde@rediffmail.com
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Image Segmentation Using Kmeans Clustering Algorithm Matlab Project Source Code

ABSTRACT
          Image segmentation is the classification of an image into different groups. Many researches have been done in the area of image segmentation using clustering. There are different methods and one of the most popular methods is k-means clustering algorithm. K -means clustering algorithm is an unsupervised algorithm and it is used to segment the interest area from the background. But before applying K -means algorithm, first partial stretching enhancement is applied to the image to improve the quality of the image. Subtractive clustering method is data clustering method where it generates the centroid based on the potential value of the data points. So subtractive cluster is used to generate the initial centers and these centers are used in k-means algorithm for the segmentation of image. 

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Mr. Roshan P. Helonde
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WhatsApp: +917276355704
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Image Steganography Using DCT Matlab Project Source Code

ABSTRACT
            Steganography is one of the methods of secret communication that hides the existence of message so that a viewer cannot detect the transmission of message and hence cannot try to decrypt it. It is the process of embedding secret data in the cover image without significant changes to the cover image. These algorithms keep the messages from stealing, destroying from unintended users on the internet and hence provide security. The proposed technique use Discrete Cosine Transform (DCT). The proposed method calculates each DC coefficient and replace with each bit of secret message. The proposed embedding method using DCT.

PROJECT OUTPUT

PROJECT VIDEO

Contact:
Mr. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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Lung Cancer Detection using Image Processing Matlab Source Code

ABSTRACT
             Lung cancer prevalence is one of the highest of cancers. One of the first steps in lung cancer diagnosis is sampling of lung tissues or biopsy. These tissue samples are then microscopically analyzed. This procedure is taken once imaging tests indicate the presence of cancer cells in the chest. Lung cancer diagnosis using lung images. One of them is that doctor still relies on subjective visual observation. A medical specialist must do thorough observation and accurate analysis in detecting lung cancer in patients. Hence, there is need for a system that is capable for detecting lung cancer automatically from microscopic images of biopsy. This method will improve the accuracy and efficiency for lung cancer detection. The aim of this research is to design a lung cancer detection system based on analysis of microscopic image of biopsy using digital image processing. Microscopic images of biopsy are feature extracted and classified.

PROJECT OUTPUT

PROJECT VIDEO

Contact:
Mr. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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Image Inpainting using Image Processing Matlab Project Source Code

ABSTRACT
               This project proposes a novel scheme for image inpainting based on discrete cosine transform (DCT). The DCT as an orthogonal transform is used in various applications. In this view the rows of a DCT matrix as the filters associated with a multiresolution analysis. In this project, propose to utilize the noise reduction property of cosine transforms for image inpainting. Current methods may available using time domain analysis by direct spatial image inpainting techniques and those that perform frequency domain analysis by indirect frequency image inpainting techniques. However, both have their own advantages and limitations. This method used for filling missing information over regions with sensible sizes, visual quality of image with frequency domain analyses. 

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Mr. Roshan P. Helonde
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WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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