LSB Steganography Hiding Secret Text Message in Cover Image Using Matlab Project Source Code

ABSTRACT

           Steganography is the one type of powerful technique which is science & art in which we have to write hidden messages, or we hide some important images, audio files, videos in this way that no-one, can find a hidden message which exists in cover images. Steganography is most strong techniques to mask the existence of unseen secret data within a cover object. Actually Stego means "Cover" graphy means "writing" that means It is nothing but we are hiding secret objects in cover image in which medium is different types of images. In practical feasible implementation practical approach would be to make the algorithm as strong as possible. In steganographed images are the most powerful objects that means cover objects, and therefore importance of image steganographed which can Embedding secret information inside images requires systematic computations. Various metrics were used to judge imperceptibility of steganography. The metrics in Matlab indicates how similar or dissimilar the stego-image compares with Cover.

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Mr. Roshan P. Helonde

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Face Recognition Using Image Processing Matlab Project Code

ABSTRACT

             Face recognition from image is a popular topic in biometrics research. Many public places usually have surveillance cameras for image capture and these cameras have their significant value for security purpose. It is widely acknowledged that the face recognition have played an important role in surveillance system as it doesn’t need the object’s cooperation. The actual advantages of face based identification over other biometrics are uniqueness and acceptance. As human face is a dynamic object having high degree of variability in its appearance, that makes face detection a difficult problem in computer vision. In this field, accuracy and speed of identification is a main issue. The goal of this project is to evaluate various face detection and recognition methods, provide complete solution for image based face detection and recognition with higher accuracy.

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Mr. Roshan P. Helonde

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Image Compression Using Modified Haar Wavelet Transform Matlab Project Source Code

ABSTRACT

           Haar transform is one of the simplest and basic transformation from the multi-resolution spectrum. The attracting features obtained from Haar transform make it a potential candidate in modern applications, such as signal and image compression. The Haar wavelet transform provides mean values that compress the image so that it takes up much less storage space, and therefore transmits faster electronically and in progressive levels of detail. The main objective of this work is to modify the weighting factor in or der to study their effects on image compression. This paper tries to implement different scale of weighting factor and study their performance on the overall system of compression. Scale of weighting factor is used in order to prevent the pixel value from exceeding their limits. Different values of weighting factor are applied, these values are spans into two range to evaluate the implemented system. 

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Mr. Roshan P. Helonde

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LSB Steganography Hiding Secret Image in Cover Image Using Matlab Project Source Code

ABSTRACT

           Steganography is the one type of powerful technique which is science & art in which we have to write hidden messages, or we hide some important images, audio files, videos in this way that no-one, can find a hidden message which exists in cover images. Steganography is most strong techniques to mask the existence of unseen secret data within a cover object. Actually Stego means "Cover" graphy means "writing" that means It is nothing but we are hiding secret objects in cover image in which medium is different types of images. In practical feasible implementation practical approach would be to make the algorithm as strong as possible. In steganographed images are the most powerful objects that means cover objects, and therefore importance of image steganographed which can Embedding secret information inside images requires systematic computations. Various metrics were used to judge imperceptibility of steganography. The metrics in Matlab indicates how similar or dissimilar the stego-image compares with Cover.

PROJECT OUTPUT

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Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Vehicle Tracking and Counting Using Matlab Project Source Code

ABSTRACT

        Monitoring highway traffic is an important application of computer vision research. In this paper, we analyze congested highway situations where it is difficult to track individual vehicles in heavy traffic because vehicles either occlude each other or are connected together by shadow. Moreover, scenes from traffic monitoring videos are usually noisy due to weather conditions and/or video compression. We present a method that can separate occluded vehicles by tracking movements of feature points and assigning over-segmented image fragments to the motion vector that best represents the fragment’s movement. Experiments were conducted on traffic videos taken from highways, and the proposed method can successfully separate vehicles in overpopulated and cluttered scenes.We present a method that can separate occluded vehicles by tracking movements of feature points and assigning over-segmented image fragments to the motion vector that best represents the fragment’s movement. Experiments were conducted on traffic videos taken from highways, and the proposed method can successfully separate vehicles in overpopulated and cluttered scenes.

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Mr. Roshan P. Helonde

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Emotion Recognition Based on Speech Sound Using Matlab Project Code || IEEE Based Project

ABSTRACT

         There are many ways of communication but the speech signal is one of the fastest and most natural methods of communications between humans. Therefore the speech can be the fast and efficient method of interaction between human and machine also. Humans have the natural ability to use all their available senses for maximum awareness of the received message. Through all the available senses people actually sense the emotional state of their communication partner. The emotional detection is natural for humans but it is very difficult task for machine. Therefore the purpose of emotion recognition system is to use emotion related knowledge in such a way that human machine communication will be improved. Emotion recognition from the speaker‟s speech is very difficult because of the following reasons: In differentiating between various emotions which particular speech features are more useful is not clear. Because of the existence of the different sentences, speakers, speaking styles, speaking rates accosting variability was introduced, because of which speech features get directly affected. The same utterance may show different emotions. Each emotion may correspond to the different portions of the spoken utterance. Therefore it is very difficult to differentiate these portions of utterance. Another problem is that emotion expression is depending on the speaker and his or her culture and environment. As the culture and environment gets change the speaking style also gets change, which is another challenge in front of the speech emotion recognition system. There may be two or more types of emotions, long term emotion and transient one, so it is not clear which type of emotion the recognizer will detect.

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Mr. Roshan P. Helonde

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Biometric Recognition Using Face, Palm, Retina and Signature using Matlab Project Code || IEEE Based Project

ABSTRACT

              Achieving high security in varied areas, biometric system has become common analysis space over past decades. Biometric system provides machine-controlled personal identification supported distinctive features of an individual. Biometric system depends on distinguishing every individual on the premise of their physiological options Face, Finger Print, Palm Print, Retina. Security will primarily be achieved by three factors: password or pin, sensible token or access card, biometric technology. Out of those three ways, biometric system is best as a result of user ought not to remember (password or pin) or keep something (smart token or access card) for identification or verification. In this project present a novel approach Biometric Recognition Using Face, Palm, Retina and Signature.

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Mr. Roshan P. Helonde

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Matlab Project Face Recognition Using Image Processing Full Source Code || IEEE Based Project

ABSTRACT

             Face recognition from image is a popular topic inbiometrics research. Many public places usually have surveillance cameras for image capture and these cameras have their significant value for security purpose. It is widely acknowledged that the face recognition have played an important role in surveillance system as it doesn’t need the object’s cooperation. The actual advantages of face based identification over other biometrics are uniqueness and acceptance. As human face is a dynamic object having high degree of variability in its appearance, that makes face detection a difficult problem in computer vision. In this field, accuracy and speed of identification is a main issue. The goal of this project is to evaluate various face detection and recognition methods, provide complete solution for image based face detection and recognition with higher accuracy.

PROJECT OUTPUT

PROJECT VIDEO

Contact:

Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com

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Breast Cancer Detection in Mammograms Matlab Project with Source Code || IEEE Based Project

ABSTRACT

            The World Health Organization's International agency for Research on Cancer in Lyon, France, estimates that more than 150 000 women worldwide die of breast cancer each year. The breast cancer is one among the top three cancers in American women. In United States, the American Cancer Society estimates that, 215 990 new cases of breast carcinoma has been diagnosed, in 2004. It is the leading cause of death due to cancer in women under the age of 65 . In India, breast cancer accounts for 23% of all the female cancers followed by cervical cancers (17.5%) in metropolitan cities such as Mumbai, Calcutta, and Bangalore. However, cervical cancer is still number one in rural India. Although the incidence is lower in India than in the developed countries, the burden of breast cancer in India is alarming. Organ chlorines are considered a possible cause for hormone-dependent cancers . Detection of early and subtle signs of breast cancer requires high-quality images and skilled mammographic interpretation. In order to detect early onset of cancers in breast screening, it is essential to have high-quality images. Radiologists reading mammograms should be trained in the recognition of the signs of early onset of, which may be subtle and may not show typical malignant features. Mammography screening programs have shown to be effective in decreasing breast cancer mortality through the detection and treatment of early onset of breast cancers.

          Emotional disturbances are known to occur in patient's suffering from malignant diseases even after treatment. This is mainly because of a fear of death, which modifies Quality Of Life (QOL). Desai et al.,reported an immuno histo chemical analysis of steroid receptor status in 798 cases of breast tumors encountered in Indian patients, suggests that breast cancer seen in the Indian population may be biologically different from that encountered in western practice. Most imaging studies and biopsies of the breast are conducted using mammography or ultrasound, in some cases, magnetic resonance (MR) imaging . Although by now some progress has been achieved, there are still remaining challenges and directions for future research such as developing better enhancement and segmentation algorithms. 

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Mr. Roshan P. Helonde

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Electronic Online Voting Machine (EVM) Matlab Project with Source Code

ABSTRACT

                    Electronic voting machine is generally used now days in some countries including India for conducting election of government in a country. But the Electronic voting machine has certain disadvantages like illegal voting and insecurity. Hence the concept of online voting system is started in some countries for conducting election. Most of the developed countries have started using online voting system but they are facing some problems in conducting it. Estonia is the only country started conducting the online voting system in national election. But the percentage of voting is only 20% to 30%. Different researchers have designed a online voting system But the system are not so much efficient in terms of accuracy and security. Also the voting system has high error rate. Hence the voting system is not flexible and can be used for specific region only. Biometric authentication is found to be more secure and accurate in certain application. Different biometric authentications like fingerprint, retina etc. can be used in designing an application to enhance the security. As fingerprint of every individual is unique it can be used for designing a voting system. Different fingerprint matching techniques has been discussed considering the FRR ratio.

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Mr. Roshan P. Helonde

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Handwritten Character Recognition Using Neural Network Matlab Project with Source Code

ABSTRACT

             Recognition of Handwritten text has been one of the active and challenging areas of research in the field of image processing and pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. In this project we focus on recognition of English alphabet in a given scanned text document with the help of Neural Networks. Using Matlab Neural Network toolbox, we tried to recognize handwritten characters by projecting them on different sized grids. The first step is image acquisition which acquires the scanned image followed by noise filtering, smoothing and normalization of scanned image, rendering image suitable for segmentation where image is decomposed into sub images. Feature Extraction improves recognition rate and mis classification. We use character extraction and edge detection algorithm for training the neural network to classify and recognize the handwritten characters.

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Mr. Roshan P. Helonde

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Email: roshanphelonde@rediffmail.com

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