Matlab Code for Audio Steganography Using Matlab - Data Hiding In Audio Using Matlab Project with Source Code

 ABSTRACT

          Information security is one of the most important factors to be considered when secret information has to be communicated between two parties. Cryptography scrambles the information, but it reveals the existence of the information. Steganography hides the actual existence of the information so that anyone else other than the sender and the recipient cannot recognize the transmission. In steganography the secret information to be communicated is hidden in some other carrier in such a way that the secret information is invisible. In this project an audio steganography technique is proposed to hide audio signal in image in the transform domain using wavelet transform. The audio signal in any format wav is encrypted and carried by the image without revealing the existence to anybody. When the secret information is hidden in the carrier the result is the stegno signal. In this work, the results show good quality stegno signal and the stegno signal is analyzed for different attacks. It is found that the technique is robust and it can withstand the attacks. The quality of the stegno signal is measured by Peak Signal to Noise Ratio (PSNR), Mean Square Error. The quality of extracted secret audio signal is measured by Signal to Noise Ratio (SNR). The results show good values for these metrics.

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Prof. Roshan P. Helonde
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Python Code for Image Steganography For Hiding Image In Image Full 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 Extract 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. In this project we perform Image Steganography for Hiding Secret Image In Cover Image Using Python.

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Matlab Code for Audio Steganography For Hiding Audio In Audio Full 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 Extract it. It is the process of embedding secret data in the cover Audio without significant changes to the cover audio. Least Significant Bit LSB algorithm keep the messages from stealing, destroying from unintended users on the internet and hence provide security. In this project we perform Audio Steganography for Hiding Secret audio In Cover audio using matlab.

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Prof. Roshan P. Helonde
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Matlab Code for Video Steganography For Hiding Audio In Video Full 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 Extract it. It is the process of embedding secret Audio file in the Cover video file without significant changes to the cover video. Least Significant Bit LSB algorithms keep the messages from stealing, destroying from unintended users on the internet and hence provide security. In this project we perform Video Steganography for Hiding Secret Audio In cover video using matlab.

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Prof. Roshan P. Helonde
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Matlab Code for Lossless Image Compression Using Huffman Algorithm Full Source Code

 ABSTRACT

            The lossless compression is that allows the original data to be perfectly reconstructed from the compressed data. Lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that probable. The main objective of image compression is to decrease the redundancy of the image data which helps in increasing the capacity of storage and efficient transmission. Image compression aids in decreasing the size in bytes of a digital image without degrading the quality of the image to an undesirable level. Image compression plays an important role in computer storage and transmission. The purpose of data compression is that we can reduce the size of data to save storage and reduce time for transmission. Image compression is a result of applying data compression to the digital image.

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Prof. Roshan P. Helonde
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Employee Attendance Monitoring from Face Recognition Using Python Source Code

 ABSTRACT

        Preserving the attendance is very crucial in all the institutes for checking the overall performance of students. Each institute has its very own method in this regard. A few are taking attendance manually using the old paper or document based approach and some have adopted techniques of automated attendance the use of few biometric techniques. There are many computerised methods to be had for this reason i.e. biometric attendance. All these methods additionally waste time due to the fact that college students or employees have to make a queue to contact their thumb on the scanning device. This gadget makes use of the face recognition approach for the computerised attendance of students in the study room environment without lectures intervention or the employee .This attendance is recorded with the aid of usage of a digital camera connected in the study room or the working environment i.e. constantly shooting photos of students or employees, discover the faces in pix and examine the detected faces with the database and mark the attendance.

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Python Code for Handwritten Digit Recognition Full Project Source code

 ABSTRACT

           Handwriting recognition is one of the compelling research works going on because every individual in this world has their own style of writing. It is the capability of the computer to identify and understand handwritten digits automatically. Because of the progress in the field of science and technology, everything is being digitalised to reduce human effort. Hence, there comes a need for handwritten digit recognition in many real-time applications. Many Machine Learning and Deep Learning Algorithms are developed which can be used for this digit classification. This project performs Digit Recognition and the analysis of accuracy of algorithms Deep Learning Algorithm.

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Prof. Roshan P. Helonde
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Python Code for Barcode Recognition using Image Processing Final Year Project

 ABSTRACT

            Barcodes are the symbols which represents the products information which is present at the backside of the product of a company. Barcodes are the thick and thin lines which are parallel to each other and it is in the form of rectangle shape. Barcodes are easy way to enter the information of the product than the manual methods. Its speed and reliability improves many operations like forwarding, packing, reception, and manufacturing. Barcodes can be found in the libraries (in the backside of book), factories, blood banks, supermarkets etc. Barcodes are the efficient way to encoding the machine readable information on most books and products. The barcode reading system is based on image processing, providing more information than laser barcode readers at a time. So, it’s started gaining more importance than laser barcode readers. In this project, we are adopting some type of barcode algorithms which segmenting the barcode patterns from images. In this project, we are going to adopt the effective barcode algorithm for various types of images.

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Prof. Roshan P. Helonde
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Real Time Face Recognition Using Python Project Source Code

  ABSTRACT

             The subject of face recognition is as old as computer vision because of the practical importance of the topic and theoretical interest from cognitive scientists. Despite the fact that other methods of identification (such as fingerprints, or iris scans) can be more accurate, face recognition has always remains a major focus of research because of its noninvasive nature and because it is people's primary method of person identification. This Project is about real time face recognition from camera Using Python. In computer literature face detection has been one of the most studied topics. Given an arbitrary image, the goal of this project is to determine real time face recognition. While this appears to be a trivial task for human beings, it is very challenging task for computers. The difficulty associated with face detection can be attributed to many variations in scale, location, view point, illumination, occlusions, etc. Although there have been hundreds of reports reported approaches for face detection, if one were asked to name a single face detection algorithm that has most impact in recent decades, it will most likely be the face detection, which is capable of processing images extremely rapidly and achieve high detection rates.

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Prof. Roshan P. Helonde
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Shape Detection and Recognition Using Image Processing Matlab Project Source Code

 ABSTRACT

               Doing image processing and especially blob analysis it is often required to check some objects' shape and depending on it perform further processing of a particular object or not. For example, some applications may require finding only circles from all the detected objects, or quadrilaterals, rectangles, etc. Human vision seems to make use of many sources of information to detect and recognize an object in a scene. At the lowest level of object recognition, researchers agree that edge and region information are utilized to extract a “perceptual unit” in the scene. Some of the possible invariant features are recognized and additional signal properties (texture or appearance) are sent to help in making the decision as to whether a point belongs to an object or not. In many cases, boundary shape information, such as the rectangular shapes of vehicles in aerial imagery, seems to play a crucial role. Local features such as the eyes in a human face are sometimes useful. These features provide strong clues for recognition, and often they are invariant to many scene variables. The study of shapes is a recurring theme in computer vision. For example, shape is one of the main sources of information that can be used for object recognition. In medical image analysis, geometrical models of anatomical structures play an important role in automatic tissue segmentation. The shape of an organ can also be used to diagnose diseases. In a completely different setting, shape plays an important role in the perception of optical illusions (we tend to see particular shapes) and this can be used to explain how our visual system interprets the ambiguous and incomplete information available in an image. Characterizing the shape of a specific rigid object is not a particularly hard problem, although using the shape information to solve perceptual tasks is not easy.

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Prof. Roshan P. Helonde
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Social Distance Detection System (Covid19) Python Project With Source Code

  ABSTRACT

          In addressing the worldwide Covid-19 pandemic situation, the process of flattening the curve for coronavirus cases will be difficult if the citizens do not take action to prevent the spread of the virus. One of the most important practices in these outbreaks is to ensure a safe distance between people in public. This paper presents the detection of people with social distance monitoring as a precautionary measure in reducing physical contact between people. This study focuses on detecting people in areas of interest using object tracking and OpenCV library for image processing. The distance will be computed between the persons detected in the captured footage and then compared to a fixed pixels' values. The distance is measured between the central points and the overlapping boundary between persons in the segmented tracking area with the detection of unsafe distances between people, alerts or warnings can be issued to keep the distance safe. In addition to social distance measure, another key feature of the system is detecting the presence of people in restricted areas, which can also be used to trigger warnings. 

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Prof. Roshan P. Helonde
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Image Steganography and Compression 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. In this project we perform DCT Based Image Steganography and Compression.

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Prof. Roshan P. Helonde
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WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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Message Encryption Decryption Using AES Algorithm / Hiding Text In Image Python Project Source Code

 ABSTRACT

            During the last decade information security has become the major issue. The encrypting and decrypting of the data has been widely investigated because the demand for the better encryption and decryption of the data is gradually increased for getting the better security for the communication between the devices more privately. The cryptography play a major role for the fulfillment for this demand. The purpose of this project is to provide the better as well as more secure communication system by enhancing the strength of Advance Encryption Standard (AES) algorithm. AES algorithm was known for providing the best security without any limitations.

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Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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Matlab Code for Brain Tumor Detection Using CNN (Convolutional Neural Network) Matlab Project Source Code

 ABSTRACT

          Brain tumors are the most common issue in children. Approximately 3,410 children and adolescents under age 20 are diagnosed with primary brain tumors each year. Brain tumors, either malignant or benign, that originate in the cells of the brain. The conventional method of detection and classification of brain tumor is by human inspection with the use of medical resonant brain images. But it is impractical when large amounts of data is to be diagnosed and to be reproducible. And also the operator assisted classification leads to false predictions and may also lead to false diagnose. Medical Resonance images contain a noise caused by operator performance which can lead to serious inaccuracies classification. In this work we used Brain Tumor Detection Using Convolutional Neural Network CNN.

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Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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Python Code for Image Encryption Decryption Using AES Algorithm Full Project Source Code

 ABSTRACT

            During the last decade information security has become the major issue. The encrypting and decrypting of the data has been widely investigated because the demand for the better encryption and decryption of the data is gradually increased for getting the better security for the communication between the devices more privately. The cryptography play a major role for the fulfillment for this demand. The purpose of this project is to provide the better as well as more secure communication system by enhancing the strength of Advance Encryption Standard (AES) algorithm. AES algorithm was known for providing the best security without any limitations.

PROJECT OUTPUT


PROJECT VIDEO

Contact:
Prof. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
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