Khaissidi Ghizlane

• Professor
• Professor (Full) at ENSA Fès

Optical character recognition (OCR) for Arabic presents unique challenges due to the script's cursive nature, contextual letter forms, multiple ligatures, the presence of diacritics, and the high variability in handwritten styles. This work introduces an enhanced Arabic handwritten word recognition architecture that integrates the attention mechani...

Handwriting recognition is essential in digital archiving, automated form processing, and data entry applications. Despite advances in Optical Character Recognition (OCR) for printed text, handwritten Arabic text recognition remains a challenging task. This paper reviews the evolution of handwriting recognition methods, from early approaches such a...

p>Ultrasound imaging is one of the most widely used non-destructive testing methods. The transducer emits pulses that travel through the imaged samples and are reflected by echo-forming impedance. The resulting ultrasonic signals usually contain noise. Most of the traditional noise reduction algorithms require high skills and prior knowledge of noi...

Crack is a condition indicator of the pavement’s structure. Generally, crack detection is an essential task for effective diagnosis of the road network. Moreover, evaluation of road quality is necessary to ensure traffic security. Since 2011, a periodic survey of approximately 57,500 km of Moroccan roads has been performed using an inspection vehic...

Parkinson’s disease (PD) affects millions of people worldwide, it dramatically affects the brain areas’ structure and functions. Therefore, it causes a progressive decline of cognitive, functional and behavioral abilities. These changes in the brain result in the degradation of motor skills’ performances. Handwriting is a daily task combining cogni...

One of the most challenging problems of ultrasonic non-destructive testing is the signal distortion caused by the presence of noise, yielding the sound wave corruption and thus degrading the ultrasonic imaging technology performance due to Time of flight methods’ loss of precision. Deep learning algorithms have proven their effectiveness in reducin...

Handwriting is a component of the complex language that came about late in the history of mankind and which develops late in human beings. Numerous works have raised changes in both the graphic and kinematic characteristics of writing. Although, age does not modify the lexical and syntactic parameters of language, it can however modify its spatial...

Parkinson’s disease (PD) is a degenerative and progressive disorder that affects the nervous system. The diagnosis of this disease remains a very important area of research since there is no subjective method of diagnosis used clinically. In this work, to address this problem, we involved a deep learning model using transfer learning from a pre-tra...

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases affecting a large population worldwide. Parkinson’s disease is characterized by rigidity, slowness of movement and tremors at rest, these syndromes are frequently manifested in the deterioration of handwriting. The aim of this article is to perform online Arabic handwriti...

Parkinson's disease (PD) is a progressive movement disorder characterized by tremors at rest, bradykinesia, and stifness. The alteration of handwriting (HW) faculties is one of the earliest motor symptoms in PD patients. This characteristic can be exploited to develop an automatic aid system for early detection of this pathologie. This article aims...

The success of any words-characters recognition system depends on board parameters such as the language (Arabic, Latin, Indi …), the document type (writing or typing), based or free-segmentation, pretreatment, features extraction and classification approaches. Within these fields, Building a robust and viable recognition system for Arabic handwritt...

Parkinson’s disease (PD) is a neurodegenerative disorder that affects a person’s movement. As the early diagnosis of the disease is crucial, the main aim of this work is to implement an online analysis system of patients’ handwriting, through computer vision and signal processing techniques, using the database collected in the neurology department...

Background and objectives Handwriting (HW) is a task that requires fine motor control and specific neuromuscular coordination. An alteration of the HW faculties represents an early motor symptom of PD which can be exploited to develop an intelligent diagnostic system of this pathology. This article aims to identify the nature of the graphic element...

In this thesis, we present a new paradigm for characterizing Parkinson's disease through the analysis of online handwriting acquired on a digital graphic tablet based on techniques and methods of machine learning and artificial intelligence. The state of the art is extensively dominated by studies carried out on Latin languages, and limited only to...

In this paper, we propose to characterize the on-line handwriting for the early detection of Parkinson’s disease. Thus, using kinematics, mechanical, and spatial features of handwriting, we are looking for the characterization of Parkinson’s disease. This paper describes the phase of the data acquisition which is currently carried out with in the N...

Abstract: The researchers have focused on the techniques used to create systems for data protection such as signature verification, investigation in crimes, handwriting mails, graphical documents analysing, human assisting, etc. Recently, several researchers have focused on creating an optimal system for data processing in handwriting documents. Th...

This paper presents an efficient word spotting system applied to handwritten Arabic documents, where images are represented with bag-of-visual-SIFT descriptors and a sliding window approach is used to locate the regions that are most similar to the query by following the query-by-example paragon. First, a pre-processing step is used to produce a be...

Parkinson's disease (PD) is the second most common neurodegenerative disease affecting significant portion of elderly population. One of the most frequent hallmarks and usually also the first manifestation of PD is deterioration of handwriting. Since the diagnosis of Parkinson's disease is difficult, researchers have worked to develop a support too...

Parkinson’s disease (PD) is one of the most common neurological diseases of the central nervous system. Its main symptom is movement disorders. The complex symptoms of PD induce difficulties for a clinical diagnosis, which require automatic early detection that allows intervening to stop its progression. In this work, we propose an automatic diagno...

Introduction L’écriture est un processus cognitif qui résulte de l’interaction entre plusieurs facteurs du développement cognitifs, linguistiques, et psychomoteurs. De ce fait, la détérioration de celle-ci est un signe de dysfonctionnement dans l’une des sphères cognitives. Objectifs Notre objectif est de développer une technique innovante, permet...

Le 3ème forum des doctorants à la faculté de Medecine de Fès. Troisième prix du meilleur court-métrage présentant le projet. https://www.youtube.com/watch?v=xPssV7chRQo&t=19s&frags=pl%2Cwn

This paper attempts to deal with the problems of query-by-example word spotting in handwritten Arabic document. This operation needs a lot of time and effort to do manual work. For this, we propose a fully non supervised methodology dedicated to the word spotting system, without using any text word or line segmentation step, because any segmentatio...

In this paper we present an unsupervised segmentation-free method for spotting and searching query, especially, for images documents in handwritten Arabic, for this, Histograms of Oriented Gradients (HOGs) are used as the feature vectors to represent the query and documents image. Then, we compress the descriptors with the product quantization meth...

Old manuscripts are a part of the richest cultural heritage and legacy of civilizations. Repetitive manual manipulation of fragile documents should be avoided as it could destroy them. Digitalization, therefore, is a convenient solution for the preservation of these manuscripts. Many digitization projects, which treat Latin scripts, have been devel...

This paper presents a query-by-example word spotting in handwritten Arabic documents, based on Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representation. First the interest points are automatically extracted from the images using SIFT detector...

This issue includes the following articles; P1150847487 B. Nagarajan and P. Balasubramanie Hybrid Feature based Object Classification with Cluttered Background Combining Statistical and Central Moment Textures P1150906627 Rajeev Ratan and Sanjay Sharma and S. K. Sharma Brain Tumor Detection based on Multi-parameter MRI Image Analysis P1150847509 G....

This issue includes the following articles; P1150812009 P.Kiran Sree and I Ramesh Babu Face Detection from still and Video Images using Unsupervised Cellular Automata with K means clustering algorithm P1150812003 K. Chougdali and M. Jedra and N. Zahid Fuzzy kernel scatter-difference discriminant analysis for face recognition P1150724001 G. Khaissid...

This paper proposes a new approach for automatic and effective segmentation of dermoscopic images. The method of segmentation is based on a pre-processing using the color structure-texture image decomposition based on Partial Differential Equations, and a step of segmentation by fuzzy clustering based algorithm. The proposed approach has been imple...

In feature-based registration approach, the feature matching step and transform model estimation step are associated and usually conducted in a sequential way. In this paper, we propose a fully non supervised methodology dedicated to the fast registration of medical images. We adopt a method that integrates the both steps into one. First, the point...

This issue includes the following articles; P1150812009 P.Kiran Sree and I Ramesh Babu Face Detection from still and Video Images using Unsupervised Cellular Automata with K means clustering algorithm P1150812003 K. Chougdali and M. Jedra and N. Zahid Fuzzy kernel scatter-difference discriminant analysis for face recognition P1150724001 G. Khaissid...

Image registration is an important problem for image processing and computer vision with many proposed applications in medical image analysis. Image registration techniques attempt to map corresponding features between two images. In this paper we propose an approach for medical images registration characterized by their great heterogeneity and com...