The project objective is to understand how convolution and FFT can be used in image processing. Images can be represented in Matlab as two-dimensional signals with corresponding frequencies using matrix representation. Through the application of fast Fourier transforms, as the frequencies are changed, image filters can be applied to make images appear clearer. An application of convolution is edge detection. Matlab is utilized by writing programs for these two mathematical algorithms.
Our project uses MATLAB to calculate the angle to a sound source. We use a speaker connected to the function generator to produce the sound, which is picked up by two microphones connected to the line-in of the computer. We then use the FFT’ function in MATLAB to find the phase shift of the peak frequencies of each microphone. We then compare the two phases to find the phase difference, which we use to calculate the approximate angle to the source.
For our final project, we will be attempting to write an RSA encryption algorithm using Matlab. The signal will ideally be from a human voice, but due to time restraints, a signal from the function generator or one created in Matlab may be used. The Matlab program will encrypt a signal and then decrypt the signal to ultimately produce the original signal. The demonstration of this program will likely involve transfer of the encrypted file to a separate PC where it will be decrypted. The general algorithm for this project will be found using outside sources.
In this project, a dual-tone multi-frequency (DTMF) detector is implemented to run basic security features of a home security system. Using matlab, a touch-tone telephone keypad is simulated by generating signals composed of two specific frequencies. A code is entered via the keypad and the signals that are generated are processed. This processing involves taking the magnitude FFT of the signal to determine the corresponding frequencies at the peaks that were generated. If these frequencies are within a specific range of those for a correct code, a feature will be activated. One feature of the system is opening and closing a garage door. This is done by outputting a dc voltage to a motor that spins either clockwise or counter clockwise. Additionally, LEDs are turned on and off to indicate that the correct code has been entered to open a door or turn on a light. If three incorrect codes are entered consecutively, an alarm will sound.
This project will implement a UPC-A barcode (the barcodes found on most products) reader using an image input and MATLAB. An image containing a barcode will be input, varying in orientation, noise level, and focus level. The Image Processing Toolbox found in MATLAB will be used to manipulate the image. The output will consist of the 12-digit value of the barcode, where each digit is expressed by a 7-bit digit system.
Four functions of a remote control car will be controlled by a human voice. The commands will be analyzed in a Matlab program that will run continuously as the user says the commands. In order to determine the user's command it is necessary to obtain the frequency components that make up the word. This will be achieved by normalizing the sound and using the FFT function. The program will then compare frequency components to a database and determine if the command matches one of the preset commands. For ease of testing and lack of a remote control car a simple circuit consisting of LEDs will light up the appropriate commands, which will be controlled by Matlab through the Kiethley A/D card.
Our final design project will be an analog equalizer. The device will consist of three separate filters, with variable resistances that allow a user to amplify various frequency levels (bass, mid and treble). Each filter will have two outputs, one consisting of the portion of the signal that is to be amplified and the other consisting of the part of the signal that will not be amplified. The signals to be amplified will be sent to the inputs of an op-amp, while the unamplified signals will be sent to the output of the op-amp. This will allow for one final output consisting of all six signal components. The device will consist of op-amps, resistors, potentiometers and capacitors and will follow the design of most commonly used equalizer schematics. Full analysis, testing and demonstration will be included in the final report.
We are designing a voice analyzing program that is specifically trained to distinctly recognize the vowels from the English language. To do this the program will analyze the frequency components of each vowel, which has three recognizable peaks when using Matlab's FFT function. The frequency components will be compared to an array database of pre-measured vowel components from earlier trials. The idea behind this technology is a simple password system that will be able to recognize the user's voice and output a green light if the correct vowel is said. The program will illuminate a green LED to acknowledging the correct vowel or a red LED to show an incorrect entry with the use of the A/D card.
A four-digit passcode consisting of digits from 0 to 9 is specified before runtime of the system. At runtime, the system requires the user to speak a four-digit passcode. A Fourier transform is conducted for each spoken digit using MATLAB. The result is manipulated and compared to previously recorded data to determine if the digit spoken is the proper digit in the passcode. A correct digit will light a corresponding green LED, while a false digit will light the corresponding red LED. Sound indicators will signify whether the entire passcode was spoken correctly or not.
A speaker is connected to a wave function generator, and a wave is emitted with a frequency of 24 kHz. Two ultrasonic sensors face the speaker, and these sensors are connected to two separate inputs of the Keithley A/D card. Utilizing MATLAB, we calculate the phases of each sensor and use the phase difference to determine the angle that the speaker is from the sensors.
Our project is to use microphones to detect a sound and then determine the location of the sound. We will use two microphones to detect the location of a sound nearby. Once they hear a sound, the approximate location will be determined by looking at the difference in the phase shift of the sound waves heard by each of the microphones. This will be done in Matlab by use of the correlation function. This will be the basis of the project; however, if we have time, we would like to try and turn this into a sort of Halloween toy. We will put a mask on a motor which will then be turned to face the location of the detected sound. The microphones will be in an independent reference from the motor, so the sound detection will be absolute, instead of relative, to the mask/motor. We will take measurements from the microphones when given sounds at known positions, so that we have a standard to compare unknown sounds to. We will need 2 microphones, a potentiometer, a relatively strong motor, and a speaker for this project.
We will design and build an audio graphic equalizer. In Matlab we will create a graphic equalizer with which the user can select which frequency bands they want to pass and which ones they want to attenuate. It will take input from audio files and allow you to apply effects to it. You will then be able to sample the output before you save it. In addition to the equilizer we will have effects such as reverb, delay, and echo. We will create a GUI that would make the interaction with the program user-friendly.