Smaine Mazouzi

Work place: University of Skikda, Algeria



Research Interests: Image Processing, Image Manipulation, Image Compression


Smaine Mazouzi

Affiliation: Associate professor at 20 aout 1955 university of Skikda, Algeria, head of the laboratory of informatics and communication of Skikda University

Address: BP 26, El Hadaik Road, 21000 Skikda, Algeria

Brief Biographical History: 

1996 - MS degree in computer science - Robotic vision

2008- Phd degree in computer science - Collaborative vision systems

2012-Informatics and Communication Laboratory Head - Skikda University

Main Works:

A New Distributed Approach for Range Image Segmentation. CIARP 2011: 296-303

Une approche multi-agent pour la segmentation d'images de profondeur à base d'objets polyédriques. Une nouvelle approche de segmentation d'images. Technique et Science Informatiques 28(3): 365-393 (2009)

A Multi-agent Approach for Range Image Segmentation with Bayesian Edge Regularization. ACIVS 2007: 449-460

Author Articles
Handwritten Character Recognition on Focused on the Segmentation of Character Prototypes in Small Strips

By Ali Benafia Smaine Mazouzi Benafia Sara

DOI:, Pub. Date: 8 Dec. 2017

The automatic recognition of handwriting is a particularly complex operation. Until now, there is no algorithm able to recognize handwriting without that; there are assumptions to take in advance to facilitate the task of the process. A handwritten text can contain letters lowercase, uppercase letters, characters sticks and digits. Therefore, it is capital to know extract and separate all these different units in order to process them with specific algorithms to their class handwriting.
In this paper, we present a system for unconstrained handwritten text recognition, which allows to achieve this operation thanks to an intelligent segmentation based on an iterative cutting in a multi-script environment.
The results obtained from the experimental protocol reach an "equal error rate" (EER) neighboring to 6%. These calculations were calculated with a relatively small base; however this same rate can be decreased with great bases. Our results are extremely encouraging for the simple reason that our approach is situated in a more general context unlike other approaches which define several non-rigid assumptions; this clearly makes the problem simpler and may make it trivial.

[...] Read more.
Other Articles