Publications Scientifiques
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Item High-Quality Synthesized Face Sketch Using Generative Reference Prior(Polska Akademia Nauk, 2024) Mahfoud, Sami; Bengherabi, Messaoud; Daamouche, Abdelhamid; Boutellaa, Elhocine; Hadid, AbdenourFace sketch synthesis (FSS) is considered as an image-to-image translation problem, where a face sketch is generated from an input face photo. FSS plays a vital role in video/image surveillance-based law enforcement. In this paper, motivated by the recent success of generative adversarial networks (GAN), we consider conditional GAN (cGAN) to approach the problem of face sketch synthesis. However, despite the powerful cGAN model’s ability to generate fine textures, low-quality inputs characterized by the facial sketches drawn by artists cannot offer realistic and faithful details and have unknown degradation due to the drawing process, while high-quality references are inacces- sible or even unexistent. In this context, we propose an approach based on Generative Reference Prior (GRP) to improve the synthesized face sketch perception. Our proposed model, that we call cGAN-GRP, leverages diverse and rich priors encapsulated in a pre-trained face GAN for generating high-quality facial sketch synthesis. Extensive experiments on publicly available face databases using facial sketch recognition rate and image quality assessment metrics as criteria demonstrate the effectiveness of our proposed model compared to several state-of-the-art methods.Item Convolutional Encoder-Decoder Network for Road Extraction from Remote Sensing Images(Institute of Electrical and Electronics Engineers, 2024) Makhlouf, Yasmine; Daamouche, Abdelhamid; Melgani, FaridIn this paper, we propose a convolutional neural network, which is based on down sampling followed by up sampling architecture for the purpose of road extraction from aerial images. Our model consists of convolutional layers only. The proposed encoder-decoder structure allows our network to retain boundary information, which is a critical feature for road identification. This feature is usually lost when dealing with other CNN models. Our design is also less complex in terms of depth, number of parameters, and memory size. It, therefore, uses fewer computer resources in both training and during execution. Experimental results on Massachusetts roads dataset demonstrate that the proposed architecture, although less complex, competes with the state-of-the-art proposed approaches in terms of precision, recall, and accuracy.Item A robust QRS detection approach using stationary wavelet transform(Springer, 2021) Belkadi, Mohamed Amine; Daamouche, AbdelhamidAccurate QRS detection is crucial for reliable ECG signal analysis and the development of automatic diagnosis tools. In this paper, we propose a simple yet efficient new algorithm for QRS detection using the Stationary Wavelet Transform (SWT). The wavelet transform has been extensively exploited for QRS detection and proved to be an efficient mathematical tool for scale analysis; it provides good frequency components estimation for the input signal and has good localization capability. The proposed procedure exploits solely the first level approximation coefficients of the wavelet transform applied to the bandpass-filtered ECG signal. Therefore, it resulted in a reduced complexity algorithm compared to the existing methods which use many decomposition levels. Thresholding has been implemented using the Pan-Tompkins procedure which is known to be very powerful. Our approach has been assessed over the MIT/BIH benchmark database, the MIT noise stress test database for noise robustness evaluation and the European ST-T database. The obtained results show competitive performance with state-of-the-art algorithms. The proposed scheme achieved a sensitivity of 99.83%, a positive predictivity of 99.94% and a detection error rate of 0.228% using Lead I MIT-BIH Database, this performance is one of the best results over this benchmark, and 99.35% of sensitivity, 99.76% of positive predictivity and detection error rate of 0.9% using the European ST-T Database, hence, our algorithm achieved high performance on Holter environment. Using the MIT noise stress test database, our algorithm achieved 98.77% of sensitivity, 91.01% of positive predictivity, and 10.12% of DER. Thus, our algorithm is robust and outperforms state-of-the-art algorithms on noisy recordingsItem IEEE GRSS Algeria chapter activities and perspectives [Chapters](IEEE, 2019) Karoui, Moussa Sofiane; Souissi, Boularbah; Daamouche, AbdelhamidThe IEEE Geoscience and Remote Sensing Society (GRSS) Algeria Chapter is the first such Chapter in the Maghreb and North Africa regions, the second on the African continent after the South Africa Chapter, and the third in the Arab world after those of Saudi Arabia and the United Arab Emirates. This Chapter was created through the joint participation of Algerian Space Agency (ASAL) researchers [in particular, researchers from the Center des Techniques Spatiales (CTS), an operational entity of the ASAL] and Algerian scientists participating in GRS fields from various Algerian universities, such as the Université des Sciences et de la Technologie Houari Boumedienne (USTHB), the Université M'Hamed Bougara (UMB), and the Université Djilali Liabès (UDL) (Figure 1). The research interests of this community range from the design of Earth observation missions (Algerian AlSat satellite missions) through the processing of remote sensing and geospatial data and the exploitation of those data in socioeconomic applicationsItem A new method for accurate QRS detection using stationary wavelet transform(Mohamed Amine Belkadi;, 2017) Belkadi, Mohamed Amine; Daamouche, AbdelhamidIt is well-known that the wavelet transform is a very useful mathematical tool for scale analysis, with very accurate frequency components estimation for the input signal. In this paper, we propose a new efficient method for QRS detection by employing the Stationary Wavelet Transform (SWT) also known as short wavelet transform. Our approach has been tested over MIT/BIH benchmark database. The obtained results are in a good agreement with the published works. Globally, we achieved a sensitivity of 99.733%, specificity of 99.922% and an error rate of 0.345% using Lead I ECGItem ECG as a biometric for individual's identification(IEEE, 2017) Sellami, Abdelkader; Zouaghi, Amine; Daamouche, AbdelhamidIn this paper, we investigate a new method to analyze electrocardiogram (ECG) signal, extract the features, for the real time human identification using single lead human electrocardiogram. The proposed system extracts special parts of the ECG signal starting from the P wave, the QRS complex and ending with the T wave for that we used the multiresolution wavelet analysis. Different features are selected and reconstructed from both amplitude and time interval of the ECG signal. The matching decisions are evaluated on the basis of correlation coefficient between the features and the Radial Basis function network classifier is introduced for validation and comparison. The performance evaluation was carried out on four ECG public databases with a total of 149 persons subjected to different physical activities and heart conditions, the preliminary results indicate that the system achieved an accuracy of 90-93%Item Components assignment problem for flow networks using MOPSO(2021) Aissou, Abdallah; Daamouche, Abdelhamid; Moatamad Refaat, HassanComponents assignment problem subject to multiple constraints is generally considered as a multiobjective components assignment problem (MCAP). In this research work, an MCAP subject to three constraints, namely the network reliability, the total assignment cost, and the total lead-time is considered and solved. The mathematical formulation of the MCAP is given based on the constraints mentioned above (network reliability, total assignment cost, and total lead-time). Furthermore, an approach based on multiobjective particle swarm optimization (MOPSO) is presented to solve the MCAP problem. The main goal is to search for the best-assigned components that maximize network reliability and minimize both the total assignment cost and the total lead-time. The results revealed that MOPSO is more efficient than other optimization approaches based on single or multiobjective genetic algorithms. In addition, there is no need to convert the problem into minimization or maximization and normalize the solutions based on RWGA or NSGA approachesItem Compact and Full Polarimetric SAR Imaging for Target Characterization(Institute of Electrical and Electronics Engineers, 2020) Bouzerar, H.; Mebrek, S.; Souissi, B.; Daamouche, AbdelhamidRecent interest in dual polarization Synthetic Aperture Radar (SAR) systems, in which a single polarization is transmitted (e.g. linear horizontal or right circular), followed by reception of two orthogonal polarization, has lead to a novel approach to dual-pol SAR, the so-called compact polarimetric imaging (CPSAR) mode. This paper provides techniques that allow construction of pseudo quad-pol information from dual-polarization SAR systems based on a few simple assumptions. Compact polarimetry showed promise of being able to reduce the complexity, cost, mass, and data rate of a SAR system while attempting to maintain many capabilities of a fully polarimetric systemItem Sift and Gabor Features for Very High Resolution Image Classification(Institute of Electrical and Electronics Engineers, 2020) Fiala, C.; Daamouche, Abdelhamidthis paper presents a new approach to extract features from high resolution images inspired by the sift descriptor and gabor features. both of these two methods are powerful when used separately or together in region-based or pixel-based classification, they brought a high accuracy. our approach was applied to classify two very high resolution images of boumerdes (algeria) and djeddah (ksa) using knn and svm. the obtained results achieved promising performance compared to using spectral information aloneItem Automatic generation of adaptive structuring elements for road identiÞcation in VHR images(Elsevier, 2018) Makhlouf, Yasmine; Daamouche, Abdelhamid