DIGITAL IMAGE PROCESSING PROJECTS
Digital Image Processing Projects are focused two dimensional and three dimensional images for processing. Different types of images are used for implementing the image processing concepts. There are intensity transformations and spatial filtering, frequency based filtering, image restoration and reconstruction, wavelet and multi-resolution processing, color image processing, morphological image processing, image compression, image representation, segmentation and object recognition.
Digital image processing projects are created and implemented using matlab simulation tool. Matlab tool was only created for developing image processing concepts in an easy manner. Image acquisition is an important and initial task performed in image processing, images are captured from some databases, datasets, cameras and some kind of sensors. According to the different types of image sources the acquisition process will be done with the help of simulation code part. In marine based acquisition, at the back of the ship needs two air guns of the energy sources.
2015 IEEE DIGITAL IMAGE PROCESSING PROJECTS
- Identification of Insulation Defects Based on Chaotic Analysis of Partial Discharge in HVDC Superconducting Cable.
- A Learning Algorithm for Bayesian Networks and Its Efficient Implementation on GPU.
- A Regression Approach to Speech Enhancement Based on Deep Neural Networks.
- Ambient assisted living communications.
- Dynamic Adjustment of Hidden Node Parameters for Extreme Learning Machine.
- Actor–Critic-Based Optimal Tracking for Partially Unknown Nonlinear Discrete-Time Systems.
- Noise Level Estimation for Model Selection in Kernel PCA Denoising.
- Secure MISO Wiretap Channels With Multiantenna Passive Eavesdropper: Artificial Noise vs. Artificial Fast Fading.
- Is Extreme Learning Machine Feasible? A Theoretical Assessment.
- Neural Networks and Support Vector Machine Algorithms for Automatic Cloud Classification of Whole-Sky Ground-Based Images.
Overview of Digital Image Processing Projects
Image restoration is mainly focused to remove noises from the particular images and also the appearance of images has been improved. To represent the images with several types of resolutions have to use establishment wavelets. Technique of compression plays an important role for providing effective and efficient results under security domain. Simulation tools are used to create morphological processing with the help of extracted image components. Greater usage of morphological process is the shape of description and representation of images.
Object Recognition is the process to recognize the factors with their features, properties and parameters. Recognition task has two types, finding a face and finding a people. People recognition process has the input of images and videos. From that we have to recognize the peoples. In face recognition process may be done with the help of face features like color, shape, texture and some geometrical based features.
Process of segmentation needs to splitting the image as many regions.
Segmentation in Digital Image Processing Projects
- Edge-Based Segmentation.
- Watershed based segmentation.
- Thresholding base segmentation.
- K-means clustering based segmentation.
- Active contours based segmentation.
Fingerprint Recognition | Digital Image Processing Projects
We provide latest Ieee Based Digital Image Processing Projects for B.E/B.Tech.Digital Image Processing Projects for M.E/M.Tech Students.
Digital image processing projects are developed and maintaining the extraordinary process behind in the image processing concepts. In digital image processing the images are continuously translate the sensed information to forming digital information. This step includes two processes are sampling and quantization. Sampling is the process of digitizing the synchronize values and quantization is the process of digitizing the values of amplitude.