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### Video 58: Transform Basics (Concepts of Orthogonal, Bi-orthogonal vectors, Basis functions & Transforms)

Hello viewers, in this video, basic background of vector algebra is explained which will help the viewer to understand how transforms are evolved. The veiwer will learn about vector inner product, vector norm, orthogonal, orthonoroml, bi-orthogonal vectors and basis functions. Also it is explained how the basis functions can create a transforms.

This video includes following contents,
• Vector inner product.
• Orthogonal vectors.
• Orthogonal and Orthonormal basis functions.
• Bi-Orthogonal and Bi-Orthonormal basis functions.
• Evolution of Transform and creating transformation matrix.
• 1D and 2D Orthogonal transforms (Real and Complex).
• 1D and 2D Bi-Orthogonal Transforms (Real and Complex).
• Numerical examples of various transforms.
• Some popular transforms.

### Video 57: Rice Grain Quality Assessment using Morphological Image Processing (Offline and Realtime mode)

Hello viewers, in this video, an implementation of rice quality assessment algorithm is shown. The proposed algorithm is based on morphological image processing. The quality of rice is estimated only on the basis of the length of rice grains. This implementation is done for both offline and online (Realtime) mode. In offline mode, images of rice grains are given to the algorithm and in real time mode, a camera is attached which takes images of rice grains and tells the outcome in real time.

This video includes following contents,
• Need of automated rice grain quality assessment.
• Steps of proposed scheme based on morphological image processing.
• Solving touching grains problem.
• MATLAB Code for proposed scheme.
• Testing in offline and online mode.

### Video 56: Pseudo Coloring (Grayscale image to Color image Conversion)

Hello viewers, In this video, the concept of Pseudo Coloring is presented. Pseudo coloring is the process of converting grayscale image into color images. This lecture covers two methods, first is Intensity Slicing with few colors and with 256 colors while second method is Color Transformation. This video includes following contents,

• What is Pseudo Coloring?
• Need of Pseudo Coloring.
• Pseudo Coloring using Intensity Slicing.
• Pseudo Coloring using Color transformation.
• MATLAB Codes for Intensity Slicing, Color Transformation

### Video 55: Discrete Fourier Transform (DFT) of 1-D Signals

Hello viewers, In this video, the basic theory of Discrete Fourier Transform (DFT) is presented. It includes background of DTFT and evolution of DFT from DTFT. It also explains that how DFT can be expressed as linear transformation for easy calculation of forward DFT and inverse DFT. Also computational complexity of DFT/ IDFT calculation is discussed and compared with FFT. The MATLAB implementation is also given by which one can find N-point DFT of any real sequence of any length. This video includes following topics,

* Introduction to Discrete Time Fourier Transform (DTFT).
* Need of Discrete Fourier Transform (DFT).
* DFT Computation method.
* DFT as linear transformation.
* Algorithm complexity.
* MATLAB Code to find N-point DFT of any sequence.

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### Video 54: Face Recognition using Wavelet Features and PCA (With MATLAB Code)

Hello viewers, In this video, a face recognition scheme is implemented using Wavelet Features and Principal Component Analysis (PCA). Here wavelets are used to extract facial features and PCA is used to reduce the size of wavelet feature vectors. The proposed scheme is very robust and capable to recognize the faces even some changes occur in faces such growing beard and mustache or putting goggles etc.
This video covers followings contents,
• Face image database (Faces94).
• Face image database preparation for training and testing.
• Finding wavelet features.
• PCA for dimension reduction.
• Training and testing procedures.
• MATLAB Code for Training.
• MATLAB Code for Testing (Discrete and Bulk).
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### Video 53: ECG based Heart Disease Diagnosis using Wavelet Features and Deep CNN (Arrhythmia detection)

Hello viewers. This is recorded video of an invited guest lecture delivered by me in an international conference held in July 2021.
This video is about heart disease diagnosis using wavelet features and deep CNN mainly focusing on Arrhythmia detection and heart rate estimation.
This video includes following contents.
• Introduction (Problem Statement).
• Basics of ECG signals and QRS Complex.
• ECG Database on PhysioNet.
• Proposed wavelet based algorithm for Heart Rate estimation and Arrhythmia detection.
• Deep CNN based approach of Arrhythmia detection.
• Conclusions.
This lecture is based on my previously published YouTube videos, which you can find on following links.

1. ECG signals Classification using CWT and Deep Neural Network in MATLAB: Click Here
2. ECG's QRS Peak Detection and Heart Rate Estimation using Discrete Wavelet Transform (DWT) in MATLAB: Click Here