Local Threshold Values Research Articles

GLCM-Based Feature Extraction for Alpha Matting on Natural Images

The main objective of this research is to determine the optimal threshold value in the unknown region in the alpha-matting operation of natural images. Alpha-mating serves to draw matte from the image used in segmentation. The alpha value is very influential on the quality of segmentation which is determined by the level of threshold value accuracy. The determination of the threshold begins by breaking the grayscale image into several sub-images using Region of Interest (RoI). Each sub-image was extracted using the Gray Level Co-occurrence Matrix (GLCM) considered by the parameters of contrast, energy, and entropy at angles of 0°, 45°, 90°, and 135 °. Each feature results in extractions, which are then averaged and normalized in each sub-image. The value is determined as the local threshold value used in the alpha matting operation. Experiments were carried out on 12 natural images from the image-mating dataset to evaluate the performance of the proposed algorithm. The increase in accuracy shows up to 63% by the measurements of experiments, compared to the calculation of adaptive threshold by using the fuzzy CMs Algorithm.

ПРИМЕНЕНИЕ ТЕХНОЛОГИЙ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА ДЛЯ ПОДДЕРЖКИ РЕШЕНИЙ РУКОВОДИТЕЛЕЙ ПРЕДПРИЯТИЙ С ИСПОЛЬЗОВАНИЕМ ГИДРОМЕТЕОРОЛОГИЧЕСКОЙ ИНФОРМАЦИИ

The article proposes ideas for applying artificial intelligence technologies in decision support tasks using hydrometeorological information. The possibilities of using artificial intelligence technologies - chatbots, knowledge bases, decision support - are considered. Chatbots are necessary for searching data on large sites and portals such as http://esimo.ru using a wide range of metadata objects and classifiers - geographical areas, observation points, types of information (actual, forecast, climatic). Knowledge bases are used to identify hazardous phenomena of different levels of danger based on local threshold values for each enterprise, as well as to provide enterprise managers with information on the possible impacts of hazardous phenomena on the activities of enterprises and the population, recommendations for decision-making.

Arsenic pollution, geochemical fractions, and leaching characteristics in soil samples from four contaminated sites in the Beijiang River Basin, South China.

To remediate historically polluted sites before their land-use changes, it is essential to understand the concentration distribution, geochemical fraction, and migratory behavior of As in soil with varied particle sizes for the use of a sieving procedure. This study investigated the amount and percentage of As in soil with different particle sizes (0.25, 0.25-1, and 1-2 mm) as well as its toxicity characteristic in leaching procedure at four previously contaminated sites in the Beijiang River Basin, South China. The results showed that the total As concentration in the collected soils ranged from 70.1 to 402.8 mg/kg, and only a few percent of soil particle samples had As contents below the local risk threshold value of 60 mg/kg. The amorphous hydrous oxide bound, crystalline hydrous oxide bound, and residual fractions (F3-F5) of the geochemical fraction of As in soil of polluted sites accounted for 82.2-95.7% of the total As distribution. However, the concentration of As in non-specifically bound fractions increased with the mass ratio of soil with coarse particle sizes due to the negative correlation of Fe-bearing minerals concentration with the mass ratio of soil with coarse particle size. According to redundancy analysis, soil with coarse particle sizes and non-specifically bound As were mostly responsible for the As concentration in the leachate. These findings confirmed that a sieving process was not suitable for the remediation of soil As at four historically contaminated sites in the Beijiang River Basin due to the high concentration of As in soil and non-negligible environmental risk of labile extractable As in soil with coarse particle size.

Coastal response to Holocene Sea-level change: A case study from Singapore

The deceleration of early to mid-Holocene (10–7 cal. ka BP) relative sea-level rise (RSLR) played a key role in transforming coastal systems from estuaries to deltas. Palaeoenvironmental reconstruction of coastal evolution provide case studies that can help project the response of modern coastal systems to future RSLR. The response of deltas to future RSLR is particularly important to South, Southeast and East Asia which collectively contain 71% of the global coastal population living below 10 m in elevation and 75% of the global coastal floodplain population. However, few Holocene studies of equatorial delta systems exist.Here, we investigate the early to mid-Holocene coastal response to decelerating rates of RSLR through paleoenvironmental reconstruction of the Kallang River Basin, Singapore. We produce a multi-proxy (sedimentology, stable carbon isotope, XRF elemental ratios) record from sediment core MSBH01B to compare with the Holocene relative sea-level record for Singapore. We identify different phases of coastal response through the interplay between accommodation space (A) driven predominantly by RSLR and sedimentation rate (S).In the early Holocene rapid RSLR coupled with low sedimentation rates (A/S = 5.1 ± 0.3) led to mangrove disappearance in the Kallang River Basin coastal area within ∼300 years (9.5–9.2 cal. ka BP). Estuarine sediments were deposited from 9.2 to 8.8 cal. ka BP during continued high rates of RSLR coupled with highest sedimentation rates (A/S = 3.1 ± 0.8) as the coastline retreated. Prodelta sediments were deposited from 8.8 to 8.2 cal. ka BP during decreasing rate of RSLR and high sedimentation rates (A/S = 4.6 ± 5.2). Delta front sediments were deposited during this delta initiation phase from 8.2 to 7.6 cal. ka BP as during a period of low and consistent RSLR and sedimentation rates (A/S = 1.7 ± 0.2). Finally, a prograding delta started forming from 7.6 to 7.2 cal. ka BP during lowest rates of RSLR and sedimentation rates (A/S = 1.7 ± 0.2). Our record provides a case study of possible responses of modern delta systems under a spectrum of predicted sea-level rise scenarios and accompanying sedimentation rates. This study provides an estimated threshold A/S value of 1.7 for coastal retreat to inform policy and mitigation/adaptation measures for Singapore and a simple methodology to obtain local threshold values of other equatorial cities built on floodplain and/or delta systems.

Estimation of Hyrcanian forests coverage using ALOS PALSAR and MODIS satellite data (2007–2017)

This study aims to monitor the extent changes of Hyrcanian forests using ALOS-/PALSAR-1 and ALOS/PALSAR-2 (PALSAR) mosaic data with HH and HV polarimetric bands from 2007 to 2017. To date, no comprehensive studies have been conducted on the total cover area of the Hyrcanian forests. This study attempts to provide specific and local threshold values for to extract the Hyrcanian forests cover through careful examination of satellite data over ten years. In this study, the acquired 57 PALSAR images were calibrated and converted to γ0 (dB) for the years 2007, 2010, and 2017. Then, the backscattering value ranges of the Hyrcanian forests were determined using the Decision Tree classification method. The backscattering values range from −14.5 to −7.2 dB and −17.5 to −8.5 dB for the years 2007 and 2010 and −18.5 to −7.5 dB for 2017 in the HV-band and from −7.5 to −14.5 dB for 2007 and 2010 and −6.2 to −12.5 dB for 2017 in the HH band correspond to forest. Finally, the results were compared with Japanese Aerospace Exploration Organization (JAXA) forest and non-forest (F/NF) maps from PALSAR data for validation purposes; the overall accuracies and Kappa coeffitients were 92.55%, 0.82% (2007), 91.14%, 0.79% (2010), and 88.19%, 0.74 (2017), respectively. This result shows that values between −7.2 and −13.5 dB are the best range for the Hyrcanian forests’ extent extraction from PALSAR image in the HV band. The output were further validated using three independent sources: (1) High-Resolution Google Earth (GE) image; (2) F/NF maps from the JAXA; and (3) MOD13Q1 Products (250 m spatial resolution). The results show good consistency with the mentioned datasets.

Hyperlocal Observations Reveal Persistent Extreme Urban Heat in Southeast Florida

Abstract Cities around the world are experiencing the effects of climate change via increasing extreme heat worsened by urbanization. Within cities, there are disparities in extreme heat exposure that are apparent in various surface and remotely sensed observations, as well as in the health impacts. There are, however, large data gaps in our ability to quantify the heat experienced by people in their daily lives across urban areas. In this paper, we use hyperlocal observations to measure heat around Miami–Dade County, Florida. Temperature and humidity measurements were collected at sites throughout the county between 2018 and 2021 with low-cost sensors. By comparing these hyperlocal observations with a National Weather Service (NWS) site at the Miami International Airport (MIA), we show that maximum temperatures are on average 6°F (3.3°C) higher and maximum heat index values are 11°F (6.1°C) higher at sites in the county than at MIA. These measurements show that many sites frequently record a heat index above the local threshold value for heat advisory. This is in contrast with the fact that few forecast advisories are issued, and there are correspondingly few exceedances of the threshold at MIA. We use these results to motivate a discussion about the issues of this particular threshold for Miami–Dade County. We highlight the need for data that are closer to residents’ lived experience to assess the impacts of heat and help inform local and regional decision-making, particularly where heat exposure may be underappreciated as a potential public health hazard.

AN ALGORITHM FOR DETECTING PRECIPITATION IN COMPUTER PROCESSING OF VIDEO IMAGES

The importance of detecting and reducing the visibility of precipitation in video images obtained by fixed cameras is shown. A statistical analysis of the geometric (area, shape factor, and orientation deviation from the frame average), and color–brightness (intensity and color saturation) characteristics of rain and snow particles is performed in order to substantiate decision rules for detecting pixels corresponding to precipitation particles. This analysis consists in obtaining distributions of the particle parameters and approximating them by known distribution laws using the family of Pearson’s curves, the Kolmogorov criterion, and the Nelder–Mead simplex algorithm. An algorithm for detecting raindrops and snowflakes in video sequences is developed, which is supposed to be used as part of an algorithm for reducing the visibility of precipitation. The proposed approach is presented in the form of a multistage classification of frame pixels into zones with moving objects and regions of a stationary background distorted and undistorted by precipitation particles in accumulated frames. Depending on the region to which the processed pixel belongs, the final decision to assign it to the class of precipitation is made using the proposed decision rules or the developed thresholding procedure with automatic determination of local threshold values. The proposed algorithm is experimentally investigated and, using a two-criteria approach, the optimal values for the number of accumulated frames for the correct operation of the algorithm are determined—100 frames for video images with rain and 140 frames for video with snow. The gain of the developed approach in comparison with the known estimates of the probabilities of false positives and false negatives is up to 1.7% and 9.1%, respectively.

From Informing Users about Disasters to Issuing a Forecast of Possible Impacts and Recommendations

Increase in the number of disasters requires the development of hydrometeorological support, the use of a new paradigm - forecast the possible impacts of disasters on the population and enterprises, and the transition from the concept of informing users to a recommendatory concept. The problem of raising the awareness of enterprise heads and the public by creating a decision support system is considered. The purpose of the research is to justify the need to create the decision support system in case of disasters, determine the place of the system in hydrometeorological support of enterprises and population. In the field of hydrometeorology collected and formalized materials on the impacts of disasters on enterprises and the population, recommendations for making decisions. Database of local threshold values of disaster indicators for enterprises and their activities depending on season, geographical area, and climate zone has been prepared.

Natural Factors on Heterogenetic Accumulations of PTEs in Sloping Farmland in a Typical Small Mountainous Watershed in Southwest China

High potential toxic element (PTE) concentrations in soils that exceed local regulatory threshold values have been reported in non-polluted mountainous areas worldwide. However, there have been few studies that have comprehensively investigated the contribution of natural factors including the parental material, pedogenesis processes and physiochemical properties of soils on the distribution of PTEs in these soils. Therefore, in this study, we studied the distribution of 13 PTEs in sloping farmland soils collected from a mountainous watershed in Guizhou Province, Southwest China. The contributions of natural influencing factors were analyzed using a geostatistical analysis and a geographic detector method. All of the PTEs were unevenly distributed, especially Sb, and the average contents of V, Cr, Co, Ni, Cu, Zn, As, Mo, Cd, Sb, Tl, Pb and Hg were 57.15, 36.20, 4.61, 12.61, 13.36, 63.50, 11.94, 0.78, 0.37, 6.44, 0.48, 27.42 and 0.36mg/kg, respectively. The proportion of samples with Cd, Hg and As exceeding the screening value of the soil pollution risk of agricultural land in China was 46.7%, 5.9% and 4.4%, respectively. Except for Cd and Pb, the q values of the PTEs calculated from the geographical detector were above 0.05, indicating that altitude changes, which affect the pedogenesis process, have a great impact on the spatial distribution. Stratigraphic factors contributed greatly to the distribution of Co, Ni and Cu, which indicates their similarity in parental material. The combined effect of clay content, topographic factors and agricultural land types had the strongest explanatory power for V, Cr, Mo and Pb. The distributions of As, Sb, Tl and Hg are strongly associated with a potential source of mercury ore, and their accumulation is also enhanced by the adsorption on soil clay. Agricultural As also contributes to its distribution.

The recurrences of cervical cancer: Possibilities of molecular prediction

The incidence of recurrence of cervical cancer ranges from 10 to 40 %. The 5-year survival rate for patients with recurrent cervical cancer is about 5–15 % against the background of current drug therapy. Clinical and morphological characteristics of the tumor process are known, which are used as markers of an unfavorable prognosis for the development of cervical cancer recurrence. The search for molecular prognostic markers of the course of cervical cancer continues.The aim. To determine the level of immune cycle proteins in patients with cervical cancer 0–IV stages, depending on the occurrence of a relapse of the disease.Materials and research methods. A retrospective analysis of previously obtained results of a study on the local level of immune cycle proteins in patients with cervical cancer was performed. Three years after follow-up, 2 groups were formed: group 1 – patients treated for cervical cancer without signs of disease progression (n = 83); group 2 – patients with cervical cancer with local or systemic recurrence (n = 18). Used statistical methods: non-parametric methods of statistics using the Kruskal – Wallis test; ROC-analysis for significant values in order to calculate threshold values; determination of the quality of the identified predictive markers by calculating the sensitivity, specificity, accuracy.Results. Local initial threshold values have a predictive value for predicting the occurrence of cervical cancer recurrence: B7.2 < 10.7 pg/ml (Se = 0.87; Sp = 0.73; Ac = 0.76; AUC = 0.78), PD-L1 ≤ 5.1 pg/ml (Se = 0.87; Sp = 0.68; Ac = 0.71; AUC = 0.76), sCD27 ≥ 32.0 pg/ml (Se = 0.75; Sp = 0.78; Ac = 0.78; AUC = 0.75).Conclusion. Determination of local levels of B7.2, PD-L1, sCD27 in patients with cervical cancer before treatment can be used to predict the development of disease recurrence during 3 years of follow-up.

Digital Transformation of the Hydrometeorological Support for the Users - a Basis for Improving the Safety of Population and Enterprises

Major directions in solving problems of adaptation of enterprises and population to natural disasters are presented. This is done with an end-to-end technology of user support which begins with observations and finishes with decision-making in the business processes of enterprises. Increasing the awareness for the business leaders and the public about possible impacts of the disasters is a need. The heads of enterprises must receive recommendations for making decisions to prevent or reduce these impacts. It is proposed to solve this problem by a digital transformation and a new paradigm of hydrometeorological support for the users. The main software components of the end-to-end technology include tools for integration of distributed and heterogeneous data by autonomously detecting the anomalies of the current values from the local threshold values. This information is delivered to the users by mobile Internet devices. An Information Panel and MeteoMonitor applications have been developed. To increase the information delivery to the enterprise heads and the public, decision support tools are created. Some tools for assessing the potential damage and calculating the preventive actions cost will be provided. It is proposed to organize a knowledge base in the form of local threshold values of disaster indicators. The knowledge base is to be created on the possible impacts of climate change and disasters on enterprises and population for various levels of danger based on climatic, observed, and predictive information.

A morphology-based radiological image segmentation approach for efficient screening of COVID-19

Computer-aided radiological image interpretation systems can be helpful to reshape the overall workflow of the COVID-19 diagnosis process. This article describes an unsupervised CT scan image segmentation approach. This approach begins by performing a morphological reconstruction operation that is useful to remove the effect of the external disturbances on the infected regions and to locate different regions of interest precisely. The optimal size of the structuring element is selected using the Edge Content-based contrast matrix approach. After performing the opening by using the morphological reconstruction operation, further noise is eliminated using the closing-based morphological reconstruction operation. The original pixel space is restored and the obtained image is divided into some non-overlapping smaller blocks and the mean intensity value for each block is computed that is used as the local threshold value for the binarization purpose. It is preferable to manually determine the range of the infected region. If a region is greater than the upper bound then that region will be considered as an exceptional region and processed separately. Three standard metrics MSE, PSNR, and SSIM are used to quantify the outcomes. Both quantitative and qualitative comparisons prove the efficiency and real-life adaptability of this approach. The proposed approach is evaluated with the help of 400 different images and on average, the proposed approach achieves MSE 307.1888625, PSNR 23.7246505, and SSIM 0.831718459. Moreover, the comparative study shows that the proposed approach outperforms some of the standard methods and obtained results are encouraging to support the battle against the COVID-19.

Identification of paddy leaf diseases based on texture analysis of Blobs and color segmentation

There are three types of paddy leaf diseases that have similar symptoms, making it difficult for farmers to identify them, namely blast, brown-spot, and narrow brown-spot. This study aims to identification paddy plant diseases based on texture analysis of Blobs and color segmentation. Blobs analysis is used to get the number of objects, area and perimeter. Color segmentation is used to find out some color parameters of paddy leaf disease such as the color of the lesion boundary, the color of the spot of the lesion, and the color of the paddy leaf lesion. To get the best results, four methods have been chosen to obtained the threshold value, Otsu threshold value, variable threshold value, local threshold value and global threshold value. The best accuracy of the four methods using threshold variables is 90.7%. The results of this study indicate that the method used has been very satisfactory in identifying paddy plant disease.

A Hybrid-Binarization Approach for Degraded Document Enhancement

Images get degraded because of unbalanced enlightenment including text-smearing, ink-bleeding, degradation of ink over time, manuscript characters from background coming out and blended with the characters of the main side etc. So, degraded-document enhancement is a challenging issue. In recent years, several binarization approaches are proposed to enhance these images. These techniques have focused on finding a suitable global threshold value or a local threshold value for every region to eliminate the degradations. A hybrid approach can be a good solution to deal with all these matters together. This paper proposes a hybrid approach of binarization for degraded documents to produce better quality result. Then, the performance of the proposed technique is evaluated using DIBCO 2010 to DIBCO 2018 databases and compared with the existing methods which confirmed that the proposed method is robust, efficient. Finally, a direction towards future works and challenges is stated.

New Proposal for Size and Size-Distribution Evaluation of Nanoparticles Synthesized via Ultrasonic Spray Pyrolysis Using Search Algorithm Based on Image-Processing Technique.

Nanoparticle properties are correlated to their size, size distribution, and shape; it is essential to accurately measure these features in the field of nanoscience. In this study, silver nanoparticles (AgNPs) were synthesized with the ultrasonic-spray-pyrolysis (USP) method from a water solution of silver nitrate. The synthesized AgNPs were characterized by Dynamic Light Scattering (DLS) analysis and Scanning Electron Microscopy (SEM) to reveal their size and size distribution. A search algorithm based on an image-processing technique to obtain particle size and particle-size distribution from SEM micrographs is proposed. In order to obtain more quantitative information and data with respect to the morphology of particles synthesized under different process parameters, SEM micrographs with a nonhomogeneous background contrast were examined via image-processing techniques in MATLAB. Due to the inhomogeneous contrast of SEM micrographs, defining an overall threshold value was insufficient in the detection of whole nanoparticles. Thus, subimages were directly created according to the maximum and minimum particle size specified by the user to determine local threshold values. The obtained results were automatically combined to represent both particle dimension and location in the SEM micrographs. We confirmed that the results of our DLS analysis, theoretical calculation, and image-processing technique were correlated with our expected results.

Road crack detection using adaptive multi resolution thresholding techniques

Machine vision is very important for ensuring the success of intelligent transportation systems, particularly in the area of road maintenance. For this reason, many studies had been focusing on automatic image-based crack detection as a replacement for manual inspection that had depended on the specialist’s knowledge and expertise. In the image processing technique, the pre-processing and edge detection stages are important for filtering out noises and in enhancing the quality of the edges in the image. Since threshold is one of the powerful methods used in the edge detection of an image, we have therefore proposed a modified Otsu-Canny Edge Detection Algorithm in the selection of the two threshold values as well as implemented a multi-resolution level fixed partitioning method in the analysis of the global and local threshold values of the image. This is then followed by a statistical measure in selecting the edge image with the best global threshold. This study had utilized the road crack image dataset that were obtained from Crackforest. The results had revealed the proposed method to not only perform better than the conventional Canny edge detection method but had also shown the maximum value derived from the local threshold of 5x5 partitioned image outperforming the other partitioned scales.

An Algorithm for Automated Separation of Trabecular Bone From Variably Thick Cortices in High-Resolution Computed Tomography Data.

Structural measurements after separation of cortical from trabecular bone are of interest to a wide variety of communities but are difficult to obtain because of the lack of accurate automated techniques. We present a structure-based algorithm for separating cortical from trabecular bone in binarized images. Using the thickness of the cortex as a seed value, bone connected to the cortex within a spatially local threshold value is identified and separated from the remaining bone. The algorithm was tested on seven biological data sets from four species imaged using micro-computed tomography (μ-CT) and high-resolution peripheral quantitative computed tomography (HR-pQCT). Area and local thickness measurements were compared to images segmented manually. The algorithm was approximately 11 times faster than manual measurements and the median error in cortical area was -4.47 ± 4.15%. The median error in cortical thickness was approximately 0.5 voxels for μ-CT data and less than 0.05 voxels for HR-pQCT images resulting in an overall difference of -28.1 ± 71.1 μm. A simple and readily implementable methodology has been developed that is repeatable, efficient, and requires few user inputs, providing an unbiased means of separating cortical from trabecular bone. Automating the segmentation of variably thick cortices will allow for the evaluation of large data sets in a time-efficient manner and allow for full-field analyses that have been previously limited to small regions of interest. The MATLAB code can be downloaded from https://github.com/TBL-UIUC/downloads.git.

Determination of thresholds values for platelet serotonin and urinary 5-HIAA concentrations for the biological diagnosis of digestive neuroendocrine tumors

Platelet serotonin and its urinary metabolite 5-HIAA (5-hydroxyindolacetic acid) are the main biomarkers measured for the detection of neuroendocrine tumors (NET). We observe in our laboratory many false positives or false negatives for the 2 assays using threshold values given by the manufacturer. We aim to determine our own local threshold values for a better detection of gastrointestinal NETs. We studied patients with measurement of platelet serotonin and/or urinary 5-HIAA in University Hospital of Tours between January 2005 and June 2016. We established an «index» cohort with 75% of patients to determine local threshold value for the 2 parameters. A "validation" cohort constituted with 25% of remaining patients allowed us to compare the performances of manufacturer's values with local threshold values. Two hundred ninety patients were included, with 19 suffering from NETs. Local threshold value for platelet serotonin was determined at 5.13 amol/platelet, the one for urinary 5-HIAA at 3.60 μmol/mmol urinary creatinine. Platelet serotonin specificity was better with local threshold value for identical sensibility (0.75). Urinary 5-HIAA sensibility was improved with local threshold value (1 vs 0.667) for identical specificity (0.902). Using our local threshold value for platelet serotonin and urinary 5-HIAA improved diagnostic performances of these biochemical markers to detect NETs.

Disentangling natural and anthropogenic impacts on groundwater by hydrogeochemical, isotopic and microbiological data: Hints from a municipal solid waste landfill

Within human-impacted areas, high levels of inorganic compounds in groundwater are broadly and preventively attributed to local anthropogenic pollution, thoroughly disregarding geogenic natural background levels. Particularly in landfills, a proper evaluation of the significant adverse environmental effects should be completed through a detailed groundwater characterization, and appropriate reference values established prior to landfill onset. However, the monitoring network may lack a full hydrogeological representativeness of the site and of the background conditions of groundwater.This study aimed at disentangling natural and anthropogenic impacts through a synoptic analysis of hydrogeochemical, isotopic and microbiological characteristics of groundwaters from a municipal solid waste landfill area in Central Italy. Samples were collected during four seasonal monitoring surveys from the mostly anoxic aquifer underlying the target area. Field parameters, inorganic and organic compounds, environmental isotopes, faecal contamination, and microbial community characteristics were determined, along with a detailed hydrogeological conceptual model. Key inorganic contaminants (As, Fe and Mn) exceeded the local threshold values in most of the sampling points, while organic contamination was generally very low. Stable isotopes suggested that groundwater originated mainly from local rainfall, except at one monitoring points where tritium levels might indicate moderate impact. Microbiological data and the microbial community characterization, assessed by flow cytometry and BIOLOG assays, provided further supportive information, also highlighting fundamental effects of groundwater quality alterations. Overall, an integrated multi-parametric approach proved suitable to distinguish geogenic and anthropogenic impacts, thus improving strategies and schemes for protection and management of groundwaters in landfills and waste related industrial areas.

Image Enhancement Background for High Damage Malay Manuscripts using Adaptive Threshold Binarization

Jawi Manuscripts handwritten which are kept at Malaysia National Library (MNL), has aged over decades. Regardless of the intensive sustainable process conducted by MNL, these manuscripts are still not maintained in good quality, and neither can easily be read nor better view. Even thought, many states of the art methods have developed for image enhancement, none of them can solve extremely bad quality manuscripts. The quality of old Malay Manuscripts can be categorize into three types, namely: the background image is uneven, image effects and image effects expand patch. The aim of this paper is to discuss the methods used to value add the quality of the manuscript. Our propose methods consist of several main methods, such as: Local Adaptive Equalization, Image Intensity Values, Automatic Threshold PP, and Adaptive Threshold Filtering. This paper is intend to achieve a better view image that geared to ease reading. Error Bit Phase achievement (TKB) has a smaller error value for proposed method (Adaptive Threshold Filtering Process / PAM) namely 0.0316 compared with Otsu’s Threshold Method / MNAO, Binary Threshold Value Method / MNAP, and Automatic Local Threshold Value Method / MNATA. The precision achievement (namely on ink bleed images) is using a proposed method more than 95% is compared with the state of the art methods MNAO, MNAP, MNATA and their performances are 75.82%, 90.68%, and 91.2% subsequently. However, this paper’s achievement is using a proposed method / PAM, MNAO, MNAP, and MNATA for correspondingly the image of ink bleed case are 45.74%, 54.80%, 53.23% and 46.02%. Conclusion, the proposed method produces a better character shape in comparison to other methods.