Predictive based hybrid ranker to yield significant features in writer identification

The contribution of writer identification (WI) towards personal identification in biometrics traits is known because it is easily accessible, cheaper, more reliable and acceptable as compared to other methods such as personal identification based DNA, iris and fingerprint. However, the production of high dimensional datasets has resulted into too many irrelevant or redundant features. These unnecessary features increase the size of the search space and decrease the identification performance. The main problem is to identify the most significant features and select the best subset of features that can precisely predict the authors. Therefore, this study proposed the hybridization of GRA Features Ranking and Feature Subset Selection (GRAFeSS) to develop the best subsets of highest ranking features and developed discretization model with the hybrid method (Dis-GRAFeSS) to improve classification accuracy. Experimental results showed that the methods improved the performance accuracy in identifying the authorship of features based ranking invariant discretization by substantially reducing redundant features

State Of The Art In Digital Paleography

Digital paleography is an approach used to assist paleographers in deciding the origin of manuscripts. This is done by recording types of writings present in old manuscripts. It uses digital representation of book hands as a tool to support paleographical analyses by, human experts. There are six types of manuscripts selected which are Arabic, Chinese, Jawi, Indian, Latin and Roman. These types of manuscripts are discussed through their current contribution in the digital paleography field. The main purpose of this paper is to discuss the current work on digital paleography for selected types of manuscripts. Thus, we identified the approaches and methods used to define the types of handwritings in old manuscript

Predictive Based Hybrid Ranker To Yield Significant Features In Writer Identification

The contribution of writer identification (WI) towards personal identification in biometrics traits is known because it is easily accessible, cheaper, more reliable and acceptable as compared to other methods such as personal identification based DNA, iris and fingerprint. However, the production of high dimensional datasets has resulted into too many irrelevant or redundant features. These unnecessary features increase the size of the search space and decrease the identification performance. The main problem is to identify the most significant features and select the best subset of features that can precisely predict the authors. Therefore, this study proposed the hybridization of GRA Features Ranking and Feature Subset Selection (GRAFeSS) to develop the best subsets of highest ranking features and developed discretization model with the hybrid method (Dis-GRAFeSS) to improve classification accuracy. Experimental results showed that the methods improved the performance accuracy in identifying the authorship of features based ranking invariant discretization by substantially reducing redundant features

Frame Removal For Mushaf Al-Quran Using Irregular Binary Region

Segmentation is a process to remove frame or frame exists in each page of some releases of mushaf Al-Quran. The fault in segmentation process affects the holiness of Al-Quran. The difficulty to identify the appearance of frame around text areas as well as noisy black stripes has caused the segmentation process to be improperly carried out. In this paper, an algorithm for detecting the frame on Al-Quran page without affecting its content is proposed. Firstly, preprocessing was carried out by using the binarisation method. Then, it was followed with the process of detecting the frame in each page. In this stage, the proposed algorithm was applied by calculating the percentage of black pixel of binary from vertical (column) to horizontal (row). The results, based on experiments on several Al-Quran pages from different Al-Quran styles, demonstrate the effectiveness of the proposed techniqu

Systematic Feature Analysis On Timber Defect Images

Feature extraction is unquestionably an important process in a pattern recognition system.A clearly defined set of features makes the identification task more effective. This paper addresses the extraction and analysis of features based on statistical texture to characterize images of timber defects.A series of procedures including feature extraction and feature analysis was executed in order to construct an appropriate feature set that could significantly distinguish amongst defects and clear wood classes.The feature set is aimed for later use in a timber defect detection system.To assess the discrimination capability of the features extracted, visual exploratory analysis and statistical confirmatory analysis were performed on defect and clear wood images of Meranti (Shorea spp.)timber species.Findings from the analysis demonstrated that utilizing the proposed set of texture features resulted in significant distinction between defect classes and clear wood

Framework Of Page Segmentation For Mushaf Al-Quran Based On Multiphase Level Segmentation

This paper presents the framework of page segmentation for Mushaf Al-Quran based on Multiphase Level Segmentation (MLS).This study focuses to (a) extract multiform frame shape by using a novel technique Neighbouring Pixel Behaviors (NPB) and (b) segment text line by using a novel technique which is Hybrid Projection Based Neighbouring Properties (HPBNP).Since Mushaf Al-Quran pages are decorated with a different type of pattern and design of a decorative frame.Thus,the decoration frame must be properly to extract out from a page of Mushaf Al-Quran first before properly get only the text of Mushaf Al-Quran regardless of its decoration heterogeneity.Therefore,NPB technique was proposed to remove multiform frame shape from the page of Mushaf Al-Quran.While the text of Mushaf Al-Quran has a several of diacritical marks,hence it will block the process of segmenting text line.Therefore,HPBNP technique was proposed for segment overlapping text line that interfered by diacritical marks or the stroke of the Arabic word. Experimental results of the proposed technique is shown in this paper

Geometrical Feature Based Ranking using Grey Relational Analysis (GRA) for Writer Identification

The author’s unique characteristic is determined by the variation of generated features from feature extraction process. Different sets of features produced are based on different feature extraction methods (local or global). Thus, the process has led to the production of high dimensional datasets that contributing to many irrelevant or redundant features. The main problem however is to find a way to identify the most significant features. The features ranking method using Grey Relational Analysis (GRA) is proposed to find the significance of each feature and give ranking to the features. This study presents the Higher-Order United Moment Invariant (HUMI) as the global feature extraction methods. The combinations of features with the higher ranking are discretized and used as the subsets of features to identify the writer. The result demonstrates that the average classification accuracy of five classifiers by using just the combination of two most significant features have yielded a better performance than using all features

A systematic literature review on regression test case prioritization

Test case prioritization (TCP) is deemed valid to improve testing efficiency, especially in regression testing, as retest all is costly. The TCP schedule the test case execution order to detect bugs faster. For such benefit, test case prioritization has been intensively studied. This paper reviews the development of TCP for regression testing with 48 papers from 2017 to 2020. In this paper, we present four critical surveys. First is the development of approaches and techniques in regression TCP studies, second is the identification of software under test (SUT) variations used in TCP studies, third is the trend of metrics used to measure the TCP studies effectiveness, and fourth is the state-of-the-art of requirements-based TCP. Furthermore, we discuss development opportunities and potential future directions on regression TCP. Our review provides evidence that TCP has increasing interests. We also discovered that requirement-based utilization would help to prepare test cases earlier to improve TCP effectiveness