Video 62: Color Edge Features and DWT based Image Retrieval (With MATLAB Code)

 

Hello viewers, in this video, Content Based Image Retrieval (CBIR) is implemented. This CBIR utilizes both the color and edge features of the images. For this purpose, Color Edge Histograms are obtained. To reduce the size of feature vector, Discrete Wavelet Transform (DWT) is also used. The simulation results show the effectiveness of the proposed algorithm for effective CBIR.     

 

This video includes following contents, 

* Introduction to Content Based Image Retrieval (CBIR).

* Color Edge Feature (Proposed  Algorithm).

* Finding Feature Vector (Training Process).

* Testing Process.

* MATLAB implementation (with MATLAB code).

* Result Analysis.

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1. Previous video:

   Color Layout Descriptor (CLD) of MPEG7 for Image Retrieval: Click Here

   

2. Previous video:

   Edge Histogram Descriptor (EHD) of MPEG7 for Image Retrieval: Click Here

   

3. Previous video:

   Content Based Image Retrieval (CBIR) using Wavelet features, CLD and EHD of MPEG7: Click Here

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Download Resources:

Image Database: Click Here

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Video 61: Time Series Prediction using ANFIS (With MATLAB Code)

 

Hello viewers, in this video, The Time Series Prediction using Adaptive Neuro-Fuzzy Inference System (ANFIS) is explained. The time series taken here is Mackey-Glass chaotic time series, which is considered as benchmark problem. The ANFIS based algorithm for time series prediction is explained in detail.     

 

This video includes following contents, 

* Introduction to time-series prediction.

* ANFIS for time-series prediction.

* Mackey-Glass chaotic time series (A benchmark).

* Time series prediction algorithm using ANFIS.

* MATLAB implementation (with MATLAB code).

* Result Analysis.

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1. Previous video:

"Fuzzy Logic Controller (FLC)": Click Here

2. Previous video:

"ANFIS (Adaptive Neuro Fuzzy Inference System)": Click Here

 

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Video 60: ANFIS: Neuro-Fuzzy Inference System (Theory and MATLAB Implementation)

 

Hello viewers, in this video, The Neuro-Fuzzy modelling highlighting ANFIS is explained. The basic theory of ANFIS is presented. Also the complete process of MATLAB implementation is given. In MATLAB implementation, the ANFIS is used as universal approximator. The two functions 1D sin(t) and 2D sin(r)/r are realized using ANFIS.   

 This video includes following contents, 

• Neuro – Fuzzy Modelling.
• Adaptive Neuro-Fuzzy Inference System (ANFIS).
• ANFIS Architecture.
• ANFIS Hybrid learning algorithm.
• ANFIS Applications.
• ANFIS as Universal Approximator (UA).
• MATLAB Implementation of ANFIS as UA (with MATLAB code).

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1. Previous video:

"Fuzzy Logic Controller (FLC)": Click Here

2. Link for research paper of Jang: Click Here 

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Video 59: Understanding Fuzzy Logic Controllers (Theory and MATLAB Implementation)

 

Hello viewers, in this video, Fuzzy Logic Controller (FLC) is explained. Along with basic theory, the complete FLC design steps are explained. An FLC for steam throttle control is designed. Also the complete process of MATLAB implementation is explained.   

 

This video includes following contents, 

* Why need controllers?

* Classical controller and Fuzzy logic controller (FLC).

* Inside Fuzzy Logic Controller (FLC).

* Design of FLC for a throttle control system.

* Fuzzification.

* Rule base implementation.

* De-fuzzification.

* Simulation of designed FLC using MATLAB. 

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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.

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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.

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Test Images: Download

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