Audio Watermarking Using Matlab Project With Source Code Final Year Project

 ABSTRACT

           Currently over the millions of digital audio files such as digital songs are copied illegally during file-sharing over the networks. It has resulted as the loss of revenue for music and broadcasting industries. The traditional protection schemes are no longer useful to protect copyright and ownership of multimedia objects. These challenges have prompted significant research in digital audio watermarking for protection and authentication. Watermarking is a technique, which is used in protecting digital information like text, images, videos and audio as it provides copyrights and ownership. The identity of the owner of the audio file can be hidden in the audio file which is called Watermark. Therefore, digital audio watermarking is the process of hiding some information into the audio file in such a way that the quality and the audibility of the audio is not affected. It helps to prevent forgery and impersonation of audio signal. Audio watermarking is more challenging than image watermarking due to the dynamic supremacy of hearing capacity over the visual field. The proposed method involves Embedding and extraction of audio signal using Least Significant Bit. The audio signal which is in .wav  format undergoes segmentation, transformation and embedding the watermarked data and at the last inverse transformation will be carried out. We attempt to develop an efficient method for hiding the information in the audio file such that the copyright information will be protected from illegal copying of the information. 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

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Fruit Classification Using CNN Python Project With Source Code | Fruit Detection Using CNN Final Year Project

 ABSTRACT

              In recent years, use of image processing has been increasing day by day in different areas such as industrial image processing, medical imaging, real time imaging, texture classification, object recognition, etc. Image processing and computer vision in agriculture is another fast growing research field. It is an important analysing tool for pre-harvest to postharvest of crops. It has lots of applications in agriculture. The cultivation of crops can be improved by the technological support. The ability to identify the fruits based on the quality in food industry is very important nowadays where every person has become health conscious. There are different types of fruits available in the market. However, to identify best quality fruits is cumbersome task. Therefore, we come up with the system where fruit is detected under natural lighting conditions. The method used is texture detection method and shape detection. For this methodology, we use image processing to detect particular eight type of fruit. This fruit detection project is implemented in python using CNN convolutional neural network.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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Plant Disease Detection Using Image Processing Matlab Project | Plant Leaf Disease Classification

 ABSTRACT

            The detection and classification of plant diseases are the crucial factors in plant production and the reduction of losses in crop yield. This project proposes an approach for plant leaf disease detection and classification on plants using image processing. 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. Identification of the plant diseases is the key to preventing the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the studies of visually observable patterns seen on the plant. Health monitoring and disease detection on plant is very critical for sustainable agriculture. It is very difficult to monitor the plant diseases manually. It requires tremendous amount of work, expertise in the plant diseases, and also require the excessive processing time. Hence, image processing is used for the detection of plant diseases. Disease detection involves the steps like image acquisition, image pre-processing, image segmentation, feature extraction and classification. This project used for the detection of plant diseases using their leaves images in matlab platform.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com

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