samy.bakheet

Dr.-Ing. Samy Sadek

Assistant Professor - Neuro-IT (Artificial Vision), Vice-Dean for Graduate Studies and Research

Faculty of Computers and Information

Address: P. O Box 82533 Sohag, Egypt

1793

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Efficient Region-Based Image Querying

2010 | Keywords Multi-level neural networks, content-based image retrieval, Feature extraction, wavelets decomposition.,
Efficient Region-Based Image Querying
Retrieving images from large and varied repositories using visual contents has been one of major research items, but a challenging task in the image management community. In this paper we present an efficient approach for region-based image classification and retrieval using a fast multi-level neural network model. The advantages of this neural model in image classification and retrieval domain will ... Read more

Toward Robust Action Retrieval in Video

2010 | Keywords Multi-level Sigmoidal Neural Network (MS, video interpretation, Human activity recognition,
Toward Robust Action Retrieval in Video
Retrieving human actions from video databases is a paramount but challenging task in computer vision. In this work, we develop such a framework for robustly recognizing human actions in video sequences. The contribution of the paper is twofold. First a reliable neural model, the Multi-level Sigmoidal Neural Network (MSNN) as a classifier for the task of action recognition is presented. ... Read more

Robust methods for hand gesture spotting and recognition using hidden markov models and conditional random fields

2010 | Keywords Hidden Markov models, Feature extraction, , Adaptation model , , conditional random fields, gesture spotting and recogniti,
Robust methods for hand gesture spotting and recognition using hidden markov models and conditional random fields
This paper proposes an automatic method that handles hand gesture spotting and recognition simultaneously. To spot meaningful gestures of numbers (0-9) accurately, a stochastic method for designing a non-gesture model with Hidden Markov Models (HMMs) versus Conditional Random Fields (CRFs) is proposed without training data. The non-gesture model provides a confidence measure that is used as an adaptive threshold to ... Read more

Two phases neural network-based system for pornographic image classification

2009 | Keywords Image classification, adult image content, ANN,
Two phases neural network-based system for pornographic image classification
Samy Sadek, U. Sayed, and B. Michaelis, “Two phases neural network-based system for pornographic image classification,” in 5th International Conference: Sciences Of Electronic,Technologies Of Information and Telecommunications (SETIT’09), (TUNISIA), pp. 1–6, March 2009. Read more

An Efficient Method for Noisy Cell Image Segmentation Using Generalized α-Entropy

2009 | Keywords α-entropy, Cell image, Entropic image segmentation,
An Efficient Method for Noisy Cell Image Segmentation Using Generalized α-Entropy
In 1953, a functional extension by A. Rènyi to generalize traditional Shannon’s entropy known as _α_-entropies was proposed. The functionalities of _α_-entropies share the major properties of Shannon’s entropy. Moreover, these entropies can be easily estimated using a kernel estimate. This makes their use by many researchers in computer vision community highly appealing . In this paper, an efficient and ... Read more

A New Method for Image Classification Based on Multi-level Neural Networks

2009 | Keywords Image classification, multi-level neural networks, Feature Extraction, wavelets decomposition.,
A New Method for Image Classification Based on Multi-level Neural Networks
In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car”, “Building”, “Mountain”, “Farm” and “Coast”. This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with ... Read more

Cubic-spline neural network-based system for image retrieval

2009 | Keywords Artificial Neural Network, Cubic Spline Function, content-based image retrieval, Color Moments,
Cubic-spline neural network-based system for image retrieval
Research in content-based image retrieval (CBIR) shows that high-level semantic concepts in image cannot be constantly depicted using low-level image features. So the process of designing a CBIR system should take into account diminishing the existing gap between low-level visual image features and the high-level semantic concepts. In this paper, we propose a new architecture for a CBIR system named ... Read more

An artificial neural network for face detection and localization in color images

2007 | Keywords skin detection, Neural Networks, Face recognition,
An artificial neural network for face detection and localization in color images
Automatic face detection and localization is a key problem in many computer vision tasks. In this paper, a simple yet effective approach for detecting and locating human faces in color images is proposed. The contribution of this paper is twofold. First, a particular reference to face detection techniques along with a background to neural networks is given. Second, and maybe ... Read more

A hybrid cascade approach for human skin segmentation

| Keywords f-HOL features, Action Recognition, Activity Recognition, Feature extraction,
A hybrid cascade approach for human skin segmentation
Inspired by the overwhelming success of Histogram of Oriented Gradients (HOG) features in many vision tasks, in this paper, we present an innovative compact feature descriptor called fuzzy Histogram of Oriented Lines (f-HOL) for action recognition, which is a distinct variant of the HOG feature descriptor. The intuitive idea of these features is based on the observation that the slide ... Read more