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Scene Text Recognition: A Review
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      The problem of text recognition and its applicability as part of images captured in the wild has gained a significant attention from the computer vision community in recent years. In contrast to the recognition of printed documents, scene text recognition is a difficult problem. Contrary to recognition of printed documents, recognizing a scene text is a challenging problem. Many researches focus on the problem of recognizing text extracted from natural scene images. Significant attempts have been made to address this problem in recent past. However, many of these attempts work on utilizing availability of strong context, which naturally limits the dictionary. This paper presents a review of recent papers related to scene text recognition in the period (2013-2020). This paper helps other researchers to understand the whole system of scene text recognition instead of reading many papers in isolation.

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Colord Image White Cracks In-Painting Method
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The gaps and cracks in an image result from different reasons and affect the images. There are various methods concerning gaps replenishment along with serious efforts and proposed methodologies to eliminate cracks in diverse tendencies. In the current research work a color image white crack in-painting system has been introduced. The proposed inpainting system involved on two algorithms. They are Linear Gaps Filling (LGF) and the Circular Gaps Filling (CGF). The quality of output image depends on several effects such as: pixels tone, the number of pixels in the cracked area and neighborhood of cracked area and the resolution the image. The quality of the output images of two methods (linear method: average Peak Signal to Noise Ratio (PS

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Effect of Successive Convolution Layers to Detect Gender
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Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

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Publication Date
Fri Feb 04 2022
Journal Name
Iraqi Journal Of Science
AHeuristic Strategy for Improving the Performance of Evolutionary Based Complex Detection in Protein-Protein Interaction Networks
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One of the most interested problems that recently attracts many research investigations in Protein-protein interactions (PPI) networks is complex detection problem. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem wherein, recently, the field of Evolutionary Algorithms (EAs) reveals positive results. The contribution of this work is to introduce a heuristic operator, called protein-complex attraction and repulsion, which is especially tailored for the complex detection problem and to enable the EA to improve its detection ability. The proposed heuristic operator is designed to fine-grain the structure of a complex by dividing it into two more complexes, each being distinguished with a core pr

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Publication Date
Wed Jul 29 2020
Journal Name
Iraqi Journal Of Science
Automatic Vehicles Detection, Classification and Counting Techniques / Survey
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Vehicle detection (VD) plays a very essential role in Intelligent Transportation Systems (ITS) that have been intensively studied within the past years. The need for intelligent facilities expanded because the total number of vehicles is increasing rapidly in urban zones. Traffic monitoring is an important element in the intelligent transportation system, which involves the detection, classification, tracking, and counting of vehicles. One of the key advantages of traffic video detection is that it provides traffic supervisors with the means to decrease congestion and improve highway planning. Vehicle detection in videos combines image processing in real-time with computerized pattern recognition in flexible stages. The real-time pro

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Epileptic Seizures Detection Using DCT-II and KNN Classifier in Long-Term EEG Signals
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     Epilepsy is one of the most common diseases of the nervous system around the world, affecting all age groups and causing seizures leading to loss of control for a period of time. This study presents a seizure detection algorithm that uses Discrete Cosine Transformation (DCT) type II to transform the signal into frequency-domain and extracts energy features from 16 sub-bands. Also, an automatic channel selection method is proposed to select the best subset among 23 channels based on the maximum variance. Data are segmented into frames of  one Second length without overlapping between successive frames. K-Nearest Neighbour (KNN) model is used to detect those frames either to ictal (seizure) or interictal (non-

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Fabrication of PVC Enrofloxacin-Selective Electrodes for Estimating Enrofloxacin in Pure Form and as Preparation Formula:
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This study explored the development and qualities of the response of electrochemical properties of enrofloxacin-selective electrodes using precipitation based on producing phosphotungstic, after utilizing a matrix of polyvinyl chloride (PVC) and dibutyl phthalate or dibutyl phosphate as a plasticizer. The resulting membrane sensors were an enrofloxacin-phosphotungstic electrode (sensors 1) and an ENR-DOP-PTA electrode (sensors 2). Linear responses of (ENR-DBPH-PTA) and (ENR-DOP-PTA) within the concentration ranges of 2.1×10-6-10-1 and 3.0×10-6-10-2 mol. L-1, respectively, for both sensors were observed. Slopes of 51.61±0.24 and 39.40± 0.16 mV/decade and pH ranges equal to 2.5-8.5

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Experimental Study on the Effect of Using Metallic Brushes on the Charging and Discharging Time of Thermal Energy Storage Unit
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Phase change materials are known to be good in use in latent heat thermal energy storage (LHTES) systems, but one of their drawbacks is the slow melting and solidification processes. So that, in this work, enhancing heat transfer of phase change material is studied experimentally for in charging and discharging processes by the addition of high thermal conductive material such as copper in the form of brushes, which were added in both PCM and air sides. The additions of brushes have been carried out with different void fractions (97%, 94% and 90%) and the effect of four different air velocities was tested. The results indicate that the minimum brush void fraction gave the maximum heat transfer in PCM and reduced the time

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Contrast enhancement of infrared images using Adaptive Histogram Equalization (AHE) with Contrast Limited Adaptive Histogram Equalization (CLAHE)
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The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign

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Publication Date
Mon Jan 10 2022
Journal Name
Iraqi Journal Of Science
Iris Outer Boundary Localization Based on Leading Edge Technique
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In recent years, the iris biometric occupies a wide interesting when talking about
biometric based systems, because it is one of the most accurate biometrics to prove
users identities, thus it is providing high security for concerned systems. This
research article is showing up an efficient method to detect the outer boundary of
the iris, using a new form of leading edge detection technique. This technique is
very useful to isolate two regions that have convergent intensity levels in gray scale
images, which represents the main issue of iris isolation, because it is difficult to
find the border that can separate between the lighter gray background (sclera) and
light gray foreground (iris texture). The proposed met

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