Performance Evaluation Methodology for Historical Document Image Binarization

Ntirogiannis, Konstantinos; Gatos, Basilis; Pratikakis, Ioannis

doi:10.1109/tip.2012.2219550

Cited by 144 publications

(84 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Only the DIBCO dataset [10] had ground-truth images available. This makes the assessment task of real-world images extremely difficult [35]. All care must be taken to guarantee the fairness of the process.…”

Section: Experiments and Resultsmentioning

confidence: 99%

A New Binarization Algorithm for Historical Documents

et al. 2018

View full text Add to dashboard Cite

Abstract:Monochromatic documents claim for much less computer bandwidth for network transmission and storage space than their color or even grayscale equivalent. The binarization of historical documents is far more complex than recent ones as paper aging, color, texture, translucidity, stains, back-to-front interference, kind and color of ink used in handwriting, printing process, digitalization process, etc. are some of the factors that affect binarization. This article presents a new binarization algorithm for historical documents. The new global filter proposed is performed in four steps: filtering the image using a bilateral filter, splitting image into the RGB components, decision-making for each RGB channel based on an adaptive binarization method inspired by Otsu's method with a choice of the threshold level, and classification of the binarized images to decide which of the RGB components best preserved the document information in the foreground. The quantitative and qualitative assessment made with 23 binarization algorithms in three sets of "real world" documents showed very good results.

show abstract

Section: Experiments and Resultsmentioning

confidence: 99%

A New Binarization Algorithm for Historical Documents

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The qualitative results that can be seen in Figure 2 correspond to various methods applied on manuscript image shown in Figure 1a. For quantitative estimation we used the well-known measures pseudo F-measure [21], PSNR [23], NRM [23][24], DRD [26], MPM [25] and geometric accuracy [27]. …”

Section: Performance Analysis With Other Methodsmentioning

confidence: 99%

Enhancement of Degraded Manuscript Images using Adaptive Gaussian Thresholding

Khetan¹,

Kejriwal²,

Indu³

2017

IJFGCN

View full text Add to dashboard Cite

show abstract

“…The popular evaluators and indices include the recall, precision, F-Measure, and accuracy [22][23][24] which are considered in this study for the evaluation of RTSSLS.…”

Section: Evaluation Of Automatic Summarymentioning

confidence: 99%

A Novel Real-Time Speech Summarizer System for the Learning of Sustainability

et al. 2015

View full text Add to dashboard Cite

As the number of speech and video documents increases on the Internet and portable devices proliferate, speech summarization becomes increasingly essential. Relevant research in this domain has typically focused on broadcasts and news; however, the automatic summarization methods used in the past may not apply to other speech domains (e.g., speech in lectures). Therefore, this study explores the lecture speech domain. The features used in previous research were analyzed and suitable features were selected following experimentation; subsequently, a three-phase real-time speech summarizer for the learning of sustainability (RTSSLS) was proposed. Phase One involved selecting independent features (e.g., centrality, resemblance to the title, sentence length, term frequency, and thematic words) and calculating the independent feature scores; Phase Two involved calculating the dependent features, such as the position compared with the independent feature scores; and Phase Three involved comparing these feature scores to obtain weighted averages of the function-scores, determine the highest-scoring sentence, and OPEN ACCESSSustainability 2015, 7 3886 provide a summary. In practical results, the accuracies of macro-average and micro-average for the RTSSLS were 70% and 73%, respectively. Therefore, using a RTSSLS can enable users to acquire key speech information for the learning of sustainability.

show abstract

Performance Evaluation Methodology for Historical Document Image Binarization

Cited by 144 publications

References 53 publications

A New Binarization Algorithm for Historical Documents

A New Binarization Algorithm for Historical Documents

Enhancement of Degraded Manuscript Images using Adaptive Gaussian Thresholding

A Novel Real-Time Speech Summarizer System for the Learning of Sustainability

Contact Info

Product

Resources

About