Category Archive: 'matlab projects for mtech students'

Intelligent autofocus with adaptive depth of field

In this paper, we propose a technique for multiregion autofocusing. The objective is to make the objects of interest at the different distance locations well focused while maintaining the shallow depth of field. Based on the image sharpness analysis of interested regions, we determine the camera’s best lens position and largest aperture size such that the depth […]

A new feature extraction method for license plate recognition

In this paper, character recognition found in license plates is described. The developed procedure is based on real license plates. The numbers are limited to ten classes (0-9). The character recognition problem is a very important problem and many people worked on implementing different methods. One of the successful set of methods to recognize characters […]

Median Filtered Image Quality Enhancement and Anti-Forensics via Variational Deconvolution

Median filtering enjoys its popularity as a widely adopted image denoising and smoothing tool. It is also used by anti-forensic researchers in helping disguise traces of other image processing operations, e.g.,image resampling and JPEG compression. This paper proposes an image variational deconvolution framework for both quality enhancement and anti-forensics of median filtered (MF) images. The proposed optimization-based framework consists of a convolution term, a […]

MRI compatibility of lower-extremity motion simulator: LoMS

This paper describes a magnetic resonance imaging (MRI) compatibility assessment of our lower-extremity motion simulator called LoMS which provides gait-like motion for a wearer within his/her lying posture during functional MRI (fMRI) imaging. We confirmed that the existence and the movement of LoMS do not decrease the fMRI image quality when the distance between LoMS and the head coil of […]

Use of Wavelet Multiresolution Analysis to Reduce Radiation Dose in Digital Mammography

This paper investigates the use of a wavelet multiresolution analysis to reduce noise in mammographicimages acquired with low levels of radiation dose. We studied the use of a wavelet denoising technique to filter the quantum noise that is incorporated in mammographic images when the radiation dose is reduced. Results were obtained by denoising a set of mammographic images acquired with […]

Parallel software implementation of recursive multidimensional digital filters for point-target detection in cluttered infrared scenes

A technique for the enhancement of point targets in clutter is described. The local 3-D spectrum at each pixel is estimated recursively. An optical flow-field for the textured background is then generated using the 3-D autocorrelation function and the local velocity estimates are used to apply high-pass velocity-selective spatiotemporal filters, with finite impulse responses (FIRs), […]

Gibbs sampling with low-power spiking digital neurons

Restricted Boltzmann Machines and Deep Belief Networks have been successfully used in a wide variety of applications including image classification and speech recognition. Inference and learning in these algorithms uses a Markov Chain Monte Carlo procedure called Gibbs sampling. A sigmoidal function forms the kernel of this sampler which can be realized from the firing statistics of […]

Image Integrity Authentication Scheme Based on Fixed Point Theory

Based on the fixed point theory, this paper proposes a new scheme for image integrity authentication, which is very different from digital signature and fragile watermarking. By the new scheme, the sender transforms an original image into a fixed point image (very close to the original one) of a well-chosen transform and sends the fixed point image (instead of the original one) to the receiver; […]

An Efficient SVD-Based Method for Image Denoising

Nonlocal self-similarity of images has attracted considerable interest in the field of image processingand led to several state-of-the-art image denoising algorithms, such as BM3D, LPG-PCA, PLOWand SAIST. In this paper, we propose a computationally simple denoising algorithm by using the nonlocal self-similarity and the low-rank approximation. The proposed method consists of three basic steps. Firstly, our method classifies similar image patches by the […]

Object recognition by effective methods and means of computer vision

The paper deals with the design and new solutions of application software with the aim to detect and recognize objects sensed by a camera. Objects of the sensed scene were determined and recognized after previous digital processing of data delivered by the camera. To this end the computer vision learning neural-based methods of feature extraction were used. The […]