Non-local means (NLM) is a popular image denoising scheme for reducing additive Gaussian noise. It uses a patch-based approach to find similar regions within a search neighborhood and estimate the denoised pixel based on the weighted average of all the pixels in the neighborhood. All the pixels are considered for averaging, irrespective of the value of their weights. This thesis proposes an imp...

This paper presents results of a mobile robot qualitative self-localisation experiment using information from cast shadows. We present results of self-localisation using two methods for obtaining the threshold automatically: in one method the images are segmented according to their grey-scale histograms, in the other the threshold is set according to a prediction about the robot’s location, giv...

High frequency (HF) radars are capable to detect and track targets at extremely long ranges. But the signal environment that includes external noise, different kinds of clutter and interference will significantly limit the detection and system capability. This paper considers a new approach to solve the ship detection problem in a complex HF radar signal environment. It uses detection procedure...

This paper presents an intensity-based iris recognition system. The system exploits local intensity changes of the visible iris textures such as crypts and naevi. The textures are extracted using local histogram equalization and the proposed ‘quotient thresholding’ technique. The quotient thresholding partitions iris images in a database such that a ratio between foreground and background of ea...

In this paper, a hybrid segmentation method for detection of masses in digitized mammograms has been developed using three parallel approaches: adaptive thresholding method, Gabor filtering and fuzzy entropy feature as a CAD scheme. The algorithm consists of the following steps: a) Preprocessing of the digitized mammograms including identification of region of interest (ROI) as candidate for ma...

A Novel hybrid segmentation method has been developed for detection of masses in digitized mammograms using three parallel approaches: adaptive thresholding method, Gabor filtering and fuzzy entropy feature as a computer-aided detection(CAD) scheme. The algorithm consists of the following steps: a) Preprocessing of the digitized mammograms including identification of region of interest (ROI) as...

Smooth James-Stein thresholding-based estimators enjoy smoothness like ridge regression and perform variable selection like lasso. They have added flexibility thanks to more than one regularization parameters (like adaptive lasso), and the ability to select these parameters well thanks to a unbiased and smooth estimation of the risk. The motivation is a gravitational wave burst detection proble...

The performance of shot detection methods in video sequences can be improved by the use of a threshold that adapts itself to the sequence statistics. In this paper we present some new techniques for adapting the threshold. We then compare the new techniques with an existing one, leading to an improved shot detection method.