The purpose of this article is to shed light on the mechanism
and the procedures of a program that classifies an input face into
any of the six basic facial expressions, which are Anger, Disgust,
Fear, Happiness, Sadness and Surprise, in addition
to normal face.
This program works by apply PCA- principal component
analysis algorithm, which is applied of one side of the face, and
depends, on contrast to the traditional studies which rely on the
whole face, on three components: Eyebrows, Eyes and Mouth.
Those out-value are used to determine the facial feature array as
an input to the neural network, and the neural network is trained by
using the back-propagation algorithm. Note that the faces used in
this study belong to people from different ages and races.
الهدف من هذا البحث هو استعمال الشبكة العصبونية ذات الانتشار العكسي BNN في تصنيف
كتل الثدي من صور الماموغرام بهدف تخفيض عدد الخزعات الجراحية غيـر الضـرورية.
قارنا في هذه الدراسة أداء تصنيف كتل الثدي في صور الماموغرام بين الشبكة العصـبونية
ذات الانت
شار العكسي (BNN (Network Neural Backpropagation و بين أطبـاء أشـعة.
دخل BNN هو الصفات الشكلية وصفات الكسوة المستخلصة من الكتل.
Considered the diagnosis of diseases using image processing is one of the most
important areas of image processing techniques used in the medical field, Where is the
digital data in the field of ophthalmology focus of researchers for automatic dete
ction of
some important diseases such as diabetic retinopathy (DR).
And is defined as damage to the retina of the eye comes as serious complications and
on the human body complications resulting from diabetes in the long term and is
considered one of the most important causes of blindness in the world and cause serious
damage to the retina.
The research aims to Assess the performance of some of the methods used in the
diagnosis of diabetic retinopathy by revealing one of the most important accompanying
pests him in the retina of the eye and is the exudates and through diagnosed in images
digital fundus through image processing techniques where this detection process
contributes in helping to early detection.
This research introduces a new approach to reduce time execution
of processing programs, by reducing the amount of processed data,
especially in applications where the priority is to the execution time
of the program over the detailed information of captured pictures,
such as detection and tracking systems.
In this paper, we processed an array which represents the
human hand image to get the characteristics of this image. So,
we used FPGA technique, and the processing operation is
partitioned into three threads which is carried out in parallel.
Each
thread is carried out using the pipeline technique by
partitioning thread into four segments. After that, we evaluated
the speedup that we get in result of using the pipeline technique
and the parallel threads. So, we have the possibility to design an
embedded system integrated into chip (SoC), and using the
mobile phones as integral devices support the software and
hardware resources.
معالجة الصور
إيماءات الصم و البكم
تعرف على الأشكال
معالجة أنبوبية
مسالك
معالجة تفرعية
دارات قابلة للبرمجة
لغة توصيف مادية
نظام مضمن
نظام ضمن شريحة
تسريع
Deaf and Mute Gestures
Images Processing
Patterns Recognition
Pipeline Processing
Threads
Parallel Processing
(Programmable Circuits (FPGA
(Hardware Description Language (VHDL
(System on Chip (SoC
المزيد..
This paper presents an algorithm for designing a system that classifies standard human facial expressions which are fear , disgust , sad , surprise , Anger , happiness , natural expression . The facial expression that is presented in the input image
of the system can be classified depending on extracting appearance features , then they entered into neural network to complete the classification process using Matlab as a programming language.