هدفنا من خلال هذه الدراسة في إطار المشروع الفصلي للسنة الرابعة إلى إلقاء الضوء على استرجاع الصور من مجموعة كبيرة بالاعتماد على محتوى صورة هدف , و قمنا بتدعيم هذه الدراسة بتطبيق ضمن بيئة الماتلاب لبرنامج بحث عن الصور المشابهة لصورة مدخلة .
و قد تركز
بحثنا على ميزتين هامتين يكاد لا يخلو منها أي نظام بحث عن الصور بالاعتماد على المحتوى و هما ميزتي الهيستوغرام اللوني و بنية الصورة texture , ووضحنا الخطوات التي يتم في ضوئها عملية الاسترجاع بدءاً من تحليل الصورة و استخلاص شعاع الواصفات الخاص فيها , و مطابقته مع أشعة الميزات الخاصة بالصور الموجودة في قاعدة البيانات ليتم ترتيب الصور بحسب مدى تشابهها من الصورة الهدف .
و تطرقت الدراسة إلى استخدام الفضاء اللوني HMMD كبديل للفضاء اللوني RGB لاستخراج واصفات البنية اللونية على اعتبار أنه نموذج لوني موجه بالمستخدم user oriented و بالتالي نضمن أن نحصل على نتائج أفضل ترضي المستخدم .
وقمنا بتدعيم الدراسة بعدد من الأشكال و الأمثلة و المخططات التي توضح محتوى الدراسة النظرية و ما قمنا بعمله في التطبيق ضمن بيئة الماتلاب .
The audio-visual speech recognition systems that rely on speech and
movement of the lips of the speaker of the most important speech
recognition systems. Many different techniques have developed in
terms of the methods used in the feature extracti
on and classification
methods.
Research proposes the establishment of a system to identify isolated
words based audio features extracted from videos pronunciations of
words in Arabic in an environment free of noise, and then add the
energy and Temporal derivative components in extracting features of
the method Mel Frequency Cepstral Coefficient (MFCC) stage.
This paper presents a new technique to extract the features of a
common case of images of the iris called off-angle iris which
taken for persons identification system. The main problem when
using biological iris measurements to identify the persons is the
difficulty of identifying and extracting features of the iris. This
problem increasing when dealing with off-angle iris and it leading
to decrease system accuracy and increase system rate error.
The speech recognition is one of the most modern technologies, which entered force
in various fields of life, whether medical or security or industrial techniques. Accordingly,
many related systems were developed, which differ from each otherin fea
ture extraction
methods and classification methods.
In this research,three systems have been created for speech recognition.They differ
from each other in the used methods during the stage of features extraction.While the first
system used MFCC algorithm, the second system used LPCC algorithm, and the third
system used PLP algorithm.All these three systems used HMM as classifier.
At the first, the performance of the speechrecognitionprocesswas studied and
evaluatedfor all the proposedsystems separately. After that, the combination algorithm was
applied separately on eachpair of the studied system algorithmsin order to study the effect
of using the combination algorithm onthe improvement of the speech recognition process.
Twokinds of errors(simultaneous errors and dependent errors) were usedto evaluate
the complementaryof each pair of the studied systems, and to study the effectiveness of the
combination on improving the performance of speech recognition process. It can be seen
from the results of the comparison that the best improvement ratio of speech recognition
has been obtained in the case of collection MFCC and PLP algorithms with recognition
ratio of 93.4%.
In this paper, the algorithm was designed for cylinders, slots and pockets extraction from
CAD models saved in STL file depending on rule-based method and graph-based method.
Besides, windows application was designed using Visual Studio C# which al
lows the user
to import CAD model and features extraction and view their geometric information
(cylinder diameter, height, cylinder center coordinates, width, height, length for slots and
pockets. In addition, all surfaces that the feature consists from.
The proposed algorithm consists from multi-steps are: dividing input model into multi
surfaces based on RegionGrowing method, next step is cylinder features extraction
depending on rule-based method, slots and bockets extraction depending on graph-based
method, calculating geometric information for each extracted feature.
The results show that the proposed algorithm can extract cylinders, slots and pockets
features from CAD models which saved in STL files and calculates geometric information
for each extracted feature.
