Video Processing MATLAB Projects

Machine Learning Techniques in Nuclear Material Detection, Drug Ranking and Video Tracking using MATLAB

The main focus of this thesis is using machine learning and data mining techniques to solve challenging problems. Three problems from different subject areas are discussed: nuclear material detection, drug ranking and target tracking in video sequences. The techniques of the three problems described are all based on an efficiently solvable variant of normalized cut, Normalized Cut Prime (or NC). The first problem concerns detecting concealed illicit nuclear material, an important part of strategies preventing and deterring nuclear terrorism. What makes this an extremely difficult task are physical limitations of nuclear radiation detectors (arising from energy resolutions and efficiency) and shielding materials terrorists would presumably use to surround the radioactive nuclear material and absorb some of the radiation, thereby reducing the strength of the detected signal.

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Bimodal Leaky Prediction for Error Resilient Source-Channel Coding and Its Adaptation to Video Coding using MATLAB

Virtually all video networking applications suffer from transmission errors. The problem is more profound for the case of traditional predictive video coding scheme where the prediction loop propagates errors through its recursive structure. Yet, this traditional scheme is left intact in most error resilient video encoding frameworks.

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Relieving the Attentional Blink in the Amblyopic Brain with Video Games using MATLAB

Video game play induces a generalized recovery of a range of spatial visual functions in the amblyopic brain. Here we ask whether video game play also alters temporal processing in the amblyopic brain. When visual targets are presented in rapid succession, correct identification of the first target (T1) can interfere with identification of the second (T2). This is known as the "attentional blink". We measured the attentional blink in each eye of adults with amblyopia before and after 40 hours of active video game play, using a rapid serial visual presentation technique. After videogame play, we observed a ~40% reduction in the attentional blink (identifying T2 200 ms after T1) seen through the amblyopic eye and this improvement in performance transferred substantially to the untrained fellow sound eye. Our experiments show that the enhanced performance cannot be simply explained by eye patching alone, or to improved visual acuity, but is specific to videogame experience. Thus, videogame training might have important therapeutic applications for amblyopia and other visual brain disorders.

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Learning-based Trimap Generation for Video Matting using MATLAB

Object extraction is a critical operation for many content-based video applications. For these applications, a robust and precise extraction technique is required. This thesis proposes an efficient and accurate method for generating a trimap for video matting. We first segment the foreground using motion information and neighboring pixel coherence via graph cuts. Also, we estimate the parameters of a Gaussian Mixture Model for the foreground and background with segmented foreground and estimated static background. Next, we classify the pixels of each frame into models by performing maximum likelihood classification and generate a trimap which is an image consisting of three regions: foreground, background and unknown. Finally, we use the trimap as a guide in spectral matting for video matting. Our experimental results show that the proposed method yields accurate and natural object boundaries.

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Automated Video Analysis of Animal Movements Using Gabor Orientation Filters using MATLAB

To quantify locomotory behavior, tools for determining the location and shape of an animal’s body are a first requirement. Video recording is a convenient technology to store raw movement data, but extracting body coordinates from video recordings is a nontrivial task. The algorithm described in this paper solves this task for videos of leeches or other quasi-linear animals in a manner inspired by the mammalian visual processing system: the video frames are fed through a bank of Gabor filters, which locally detect segments of the animal at a particular orientation. The algorithm assumes that the image location with maximal filter output lies on the animal’s body and traces its shape out in both directions from there. The algorithm successfully extracted location and shape information from video clips of swimming leeches, as well as from still photographs of swimming and crawling snakes. A Matlab implementation with a graphical user interface is available online, and should make this algorithm conveniently usable in many other contexts.

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Wavelet based Image Compression on the Texas Instrument Video Processing Board TMS320dM6437 using MATLAB

Time has become a crucial issue in today’s lifestyle and to keep up the pace with the world we need to come up with technologies that can process things faster. With high speed technology in image processing industry, the demand of good quality data is increasing rapidly. The usage of image and streaming of video on internet have increased exponentially. In addition, more storage capacity and more bandwidth as HD (High Density) image and video have become more and more popular. In this project, mainly I demonstrated two different methods of image compression DCT based image compression and WAVELET based image compression on JPEG2000 image standard. I designed DCT based image compression and WAVELET based image compression codes in matlab and compared their results. After that, I implemented the wavelet algorithm using C and C# in visual studio to verify the design. Finally I implemented the same algorithm on TI’s digital signal processing board EVM320DM6437, based on C language. In addition, for implementing discrete wavelet transform on EVM 320DM6437 board, I captured the image frame from a video signal. Then, I extracted the Y v components of the image. Then I used Code Composer Studio software to implement the code written in C language to successful display the compression result on Television.

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