Hamid Abrishami Moghaddam

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Commonly used brain templates are based on adults' or children's brains. In this study, we create a neonatal brain template. This becomes necessary because of the pronounced differences not only in size but even more importantly in geometrical proportions of the brains of adults and children as compared to the ones of newborns. The template is created based(More)
In this paper, a new approach for content-based image indexing and retrieval is presented. The proposed method is based on a combination of multiresolution analysis and color correlation histogram of the image. According to the new algorithm, the wavelet coefficients of the image are computed first using Daubechies3 wavelet. Then, monodimensional color(More)
Recommended by Nikolaos V. Boulgouris This paper presents a novel biometric identification system with high performance based on the features obtained from human retinal images. This system is composed of three principal modules including blood vessel segmentation, feature generation, and feature matching. Blood vessel segmentation module has the role of(More)
In the last few years, we have witnessed an explosion in applications of sparse representation, the majority of which share the need for finding sparse solutions of underdetermined systems of linear equations (USLE's). Based on recently proposed smoothed κ ଴-norm (SL0), we develop a noise-tolerant algorithm for sparse representation, namely Robust-SL0,(More)
In this paper, a new algorithm called Gabor wavelet correlogram (GWC) is proposed for image indexing and retrieval. GWC is an effort to extend our former wavelet correlogram algorithm by introducing rotation invariant features using Gabor wavelets. We also present some ideas in order to handle effectively the redundancy problem due to non-orthogonal(More)
Nowadays, automatic extraction of man-made objects such as buildings and roads in urban areas has become a topic of growing interest for photogrammetric and computer vision community. Researches in this domain started from late 1980s and used quite different types of source images ranging from single intensity images, color images, laser range images to(More)
Optimization of content-based image indexing and retrieval (CBIR) algorithms is a complicated and time-consuming task since each time a parameter of the indexing algorithm is changed, all images in the database should be indexed again. In this paper, a novel evolutionary method called evolutionary group algorithm (EGA) is proposed for complicated(More)
This paper presents a fully automated face recognition system with incremental learning ability that has the following two desirable features: one-pass incremental learning and automatic generation of training data. As a classifier of face images, an evolving type of neural network called Resource Allocating Network with Long-Term Memory (RAN-LTM) is(More)