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Qin Seal Script Character Recognition with Fuzzy and Incomplete Information

The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a series of preprocessing operations, the oriented gradient histograms (HOG) features are extracted from the images. During model training, different weights are assigned to classes with varying sample quantities to address the issue of class imbalance and improve the model's classification accuracy. Results show that the model achieves an accuracy of 95.30%. This research can help historians quickly identify and extract the text content on newly discovered Qin slip cultural relics, shortening the cycle of building a historical database.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Optical Character Recognition Using Active Contour Segmentation

Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could b

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Utilization of Edge Information in Handwritten Numerals Recognition

The recognition of handwritten numerals has many applications in automatic identification and cognition. This research contains three experimented scenarios to recognize the handwritten English (i.e. Arabic) numerals. In the first scenario the bilinear interpolation of the image is used, while in the second scenario and after the bilinear interpolation is being applied, the Sobel operators are applied on the resulted interpolated image. In the third scenario which represents the last one, the effect of normalization of image dimensions is tested. 550 images of handwritten numerals were tested. Three types of tests were conducted for each scenario namely: trained-set test, not-trained-set test and comprehensive-set test. Depending on the

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Publication Date
Sun Sep 29 2019
Journal Name
Iraqi Journal Of Science
A Design of a Hybrid Algorithm for Optical Character Recognition of Online Hand-Written Arabic Alphabets

     The growing relevance of printed and digitalized hand-written characters has necessitated the need for convalescent automatic recognition of characters in Optical Character Recognition (OCR). Among the handwritten characters, Arabic is one of those with special attention due to its distinctive nature, and the inherent challenges in its recognition systems. This distinctiveness of Arabic characters, with the difference in personal writing styles and proficiency, are complicating the effectiveness of its online handwritten recognition systems. This research, based on limitations and scope of previous related studies, studied the recognition of Arabic isolated characters through the identification o

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization

The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Using financial and non-financial information ) SASB standards) to enhance investor confidence

Companies seek to enhance investor confidence by achieving the highest level of transparency in disclosure of financial and non-financial information (SASB standards) for Iraqi insurance companies listed on the financial market. The aim of the research is to identify the extent of the ability of financial and non-financial information to enhance transparency in reporting, which is reflected in Investor confidence. And the standards of sustainability development accounting issued by (SASB) through the electronic questionnaire that was distributed. Companies seek to achieve a set of goals, the most important of which is to enhance investor confidence by improving transparency in disclosure. Concerning the employment of financial an

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Publication Date
Fri Jan 02 2009
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Complete and Incomplete Revascularization of patients with Non-ST-Elevation Acute Coronary Syndrome using Angioplasty and Stenting.

Background: Angioplasty and stenting; Percutaneous coronary intervention (PCI) has become important tool of Reascularizing patients with stable angina and Acute ST-Elevation Myocardial Infarction, while their role in Non ST-elevation Acute coronary syndrome is expanding.

Objestives: The aim was to study the outcome of complete and incomplete Revascularization, by PCI, of pts with NSTE-ACS, and the effect of the traditional risk factors and their relation to the number of stents.

Patients and Methods:- After stabilization 115 out of 142 consecutive hospital admissions with Non St-Elevation Acute Coronary Syndrome were revascularized Percutanously. 

Re

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