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Real-Night-time Road Sign Detection by the Use of Cascade Object Detector
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     Variations in perspective, illumination, motion blur, and weatherworn degeneration of signs may all be essential factors in road-sign identification. The current research purpose is to evaluate the effectiveness of the image processing technique in detecting road signs as well as to find the appropriate threshold value range for doing so. The efficiency of the cascade object detector in detecting road signs was tested under variations of speed and threshold values. The suggested system involved using video data to calculate the number of frames per second and creating an output file that contains the specified targets with their labels to use later in the final process (i.e., training stage). In the current research, two videos captured some types of traffic signs (40, 60, 80, and cross signs) in Palestine and Al-Rubaie streets during night time in Baghdad city. The practical significance is demonstrated here by using the optimal threshold value for more accurate object detection. Through an increase in threshold values, results show that the highest precision value, which is equal to one, occurred for crossroad sign relations with stable behavior, followed by 80 (i.e., 1-0.824) and 60-speed signs (i.e., 1-0.315), respectively, with positive relationships, and ended by speed sign 40, which witnessed a reverse relationship with increasing threshold values until the breakdown case took place, which usually occurred above the threshold value equal to thirty (i.e., 0.471-0.134). 

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Publication Date
Sun Sep 01 2013
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Real Time Motion Detection in Surveillance Camera Using MATLAB
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Surveillance cameras are video cameras used for the purpose of observing an area. They are often connected to a recording device or IP network, and may be watched by a security guard or law enforcement officer. In case of location have less percentage of movement (like home courtyard during night); then we need to check whole recorded video to show where and when that motion occur which are wasting in time. So this paper aims at processing the real time video captured by a Webcam to detect motion in the Scene using MATLAB 2012a, with keeping in mind that camera still recorded which means real time detection. The results show accuracy and efficiency in detecting motion

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Review on Vision Based Real Time Fingertip Detection Approaches
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    Computer vision is an emerging area with a huge number of applications. Identification of the fingertip is one of the major parts of those areas. Augmented reality and virtual reality are the most recent technological advancements that use fingertip identification. The interaction between computers and humans can be performed easily by this technique. Virtual reality, robotics, smart gaming are the main application domains of these fingertip detection techniques. Gesture recognition is one of the most fascinating fields of fingertip detection. Gestures are the easiest and productive methods of communication with regard to collaboration with the computer. This analysis examines the different studies done in the field of

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Rapid Direct Detection and Differentiation of Mycobacterium tuberculosis complex in Sputum by Real-Time PCR
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Tuberculosis status as the second leading causes of significant morbidity and mortality from an infectious disease worldwide, after human immunodeficiency virus (HIV). Sample collection was conducted at the Institute of Chest and Respiratory Diseases/Baghdad Medical City in Baghdad. The collection interval was from August to October 2014, 629 suspected TB patients were examined during this period. The results revealed among total 629 specimens, 56 (8.9%) of the specimens were positive by direct examination and 573 (91.1%) negative specimens by smear microscopy. Fifty six DNA samples were extracted from positive ZN smears of sputum specimens and 40 samples from healthy persons (as control) were subjected to molecular diagnosis by real tim

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Publication Date
Thu Dec 30 2021
Journal Name
Iraqi Journal Of Science
Automatic Object Detection, Labelling, and Localization by Camera’s Drone System
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This work explores the designing a system of an automated unmanned aerial vehicles (UAV( for objects detection, labelling, and localization using deep learning. This system takes pictures with a low-cost camera and uses a GPS unit to specify the positions. The data is sent to the base station via Wi-Fi connection.

The proposed system consists of four main parts. First, the drone, which was assembled and installed, while a Raspberry Pi4 was added and the flight path was controlled. Second, various programs that were installed and downloaded to define the parts of the drone and its preparation for flight. In addition, this part included programs for both Raspberry Pi4 and servo, along with protocols for communication, video transmi

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Automatic Detection and Recognition of Car Plates Based on Cascade Classifier
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The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the ac

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Real-Time PCR Detection of Respiratory Syncytial virus (RSV) among Adults with Pneumonia
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This study aimed to confirm the presence of RSV using real-time PCR in nasal
and throat swabs which had no visible cytopathic effect in tissue culture technique
from adults of moderate-to-severe pneumonia with influenza-like illness. Results of
real-time RT-PCR found that viral RNA in 11.63% (5/43) of adult with pneumonia
and flu-like illness symptoms. A significant incidence of RSV infection in Dec. and
Jan. 2014 was appeared among patients aged more than 45 years. The results
showed that viral load significantly associated with disease severity. In conclusion,
multiplex RT-PCR is recommended to diagnose RSV and influenza viruses in
winter season in older patients with pneumonia and can decrease sever illness in

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Comparison between HSV-1 Ag detection techniques by ELISA and real-time PCR in breast cancer patients suffering from periodontitis
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Background: Periodontitis is a long-standing infection that destroys the gums, periodontal ligaments, and the alveolar bone that supports the teeth. Inflammation of the gums and chronic periodontitis are both caused by the bacteria in the dental plaque and the herpes viruses, especially types 1 and 2 of the herpes simplex virus.

Objectives: To compare the ELISA and real-time PCR as ways to detect the herpes simplex virus in breast cancer pat

J Fac Med Baghdad

2023; Vol.65, No. 3

Received:March., 2023

Accepted: June. 2023

Published: Oct. 2023

 

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Mechanical Engineering Research And Developments
Real-time control of robotic hand by human hand at low cost
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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Object Detection and Distance Measurement Using AI
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Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
Foreground Object Detection and Separation Based on Region Contrast
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Foreground object detection is one of the major important tasks in the field of computer vision which attempt to discover important objects in still image or image sequences or locate related targets from the scene. Foreground objects detection is very important for several approaches like object recognition, surveillance, image annotation, and image retrieval, etc. In this work, a proposed method has been presented for detection and separation foreground object from image or video in both of moving and stable targets. Comparisons with general foreground detectors such as background subtraction techniques our approach are able to detect important target for case the target is moving or not and can separate foreground object with high det

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