This blog post provides an list of DSP Projects for Engineering students using TMS Processor and Matlab,Students can implement these Digital signa procesing algorithms on the hardware.
DSP projects using TMS320C6745
Median Filter is implemented with Dsp TMS320C6745 hardware setup and software program in C code as well as used MatLab too. Whereas median filter are used wide range of application in Digital Image Processing. The main Feature of Median Filter is used to reduce the salt and pepper noise in Digital image.The main feature of DSP processor is their 32 bit floating point, processing speed and external memory interface. This brings very fast execution and implenting the algorithm in c code without changing the hardware setup.The Main tools which we used are Code Composer Studio v4, TYRO TMS320C6745 kit and MATLAB.
Video Tracking using TMS320C6745 DSP Processor
Object identification and tracking applications of pattern recognition at video rates is a problem of wide interest, with previous attempts limited to very simple threshold or correlation (restricted window) methods. New high-speed algorithms together with fast digital hardware have produced a system for missile and aircraft identification and tracking that possesses a degree of “intelligence” not previously implemented in a real-time tracking system. This dsp project emphasizes the practical aspects of the system and discusses the techniques used to achieve real-time video tracking.
Sobel Edge Detection using TMS320C6745 DSP
Edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. Sobel which is a popular edge detection algorithm is considered in this work. The Sobel operator performs a 2-D spatial gradient measurement on images. It uses a pair of horizontal and vertical gradient matrices whose dimensions are 3×3 for edge detection operations. This dsp project demonstrate how to build a Sobel detector using texas dsp processor.
Wavelet Transform using TMS320C6745 DSP
Signal compression can be obtained by wavelet transformation of integer input data followed by quantification and coding. As the quantification is usually lossy, the whole compression/decompression scheme is lossy too. We define a critical wavelet coefficient quantification, i.e., the coarsest quantification that allows perfect reconstruction. This is demonstrated for the Haar transform and for arbitrarily smooth wavelet transforms derived from it. The new integer wavelet transform allows implementation of multiresolution subband compression schemes, in which the decompressed data are gradually refined, retaining the option of perfect reconstruction.
Image Fusion using TMS320C6745 DSP
Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems.In this project we use DSP processor to implement the algorithms
In this project text are embedded into audio file without loss of audio quality, and while extraction we get the embedded text back.