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BHOS Tezisler 2022 17x24sm

THE 3
rd
 INTERNATIONAL SCIENTIFIC CONFERENCES OF STUDENTS AND YOUNG RESEARCHERS 
dedicated to the 99
th
anniversary of the National Leader of Azerbaijan Heydar Aliyev
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is detected and the status changes to Tracking (2
nd
picture). Except this, 
another valuable information as the number of people entered/exited and 
how many there are inside and total number passed is counted and 
displayed. 
The previously mentioned issues can be avoided and fixed in further 
versions of the program via including other related tools and more complex. 
Needless to mention, that the code can be updated to detect other objects, 
such as other means of transport, animals, household items and others 
included in the imported library. 
References 
[1] D. Cochard, "MobilenetSSD : A Machine Learning Model for Fast Object Detection," 2021.
[2] U. Michelucci, "Advanced Applied Deep Learning: Convolutional Neural Networks and 
Object Detection," 2019.
[3] J. Howse, "OpenCV Computer Vision with Python: Learn to capture videos, manipulate 
images, and track objects with Python using the OpenCV Library," 2013.
[4] "SciPy documentation".
RETINAL FUNDUS IMAGE BLOOD VESSEL SEGMENTATION 
FOR MEDICAL DIAGNOSIS 
Samra Huseynova, Fidan Mahmudova
Baku Higher Oil School 
Baku, Azerbaijan 
samra.huseynova.std@bhos.edu.az; 
 fidan.mahmudova.std@bhos.edu.az 
Supervisor: PhD, Associate Professor Leyla Muradkhanli 
Keywords: 
contrast limited histogram equalization, principal component analysis, DRIVE 
The morphology of blood vessels in retinal fundus images can be an 
important indicator of diseases which have direct impact on eyes, like 
malaria, glaucoma, hypertension and diabetic retinopathy. In this case 
quality of the segmentation plays an essential role to obtain accurate results. 
Since different fields can benefit from analysis of retinal blood vessels,we 
believe that it is worthful to develop the best method for obtaining precise 
map of tiny capillaries with the help of some high level image processing 
techniques and mathematical tools. So, our main objective is to fulfill the task 
of retinal fundus image blood vessel segmentation through several 
procedures to be further used for medical diagnosis. 



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