Integral ratio: a new class of global thresholding techniques for handwriting images

Yan, Shuicheng; Leedham, C.G.

doi:10.1109/34.784289

Cited by 107 publications

(56 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The apparent bleed-through suppression clearly improves the human legibility of the document. To show also the advantages of orthogonalization versus an improvement of the performance of OCR systems, in Figure 4 we report the results of applying the QIR optimal thresholding technique [12] to the grayscale document scan and to the orthogo- nalization output. As is seen, optimal thresholding has been much more effective on the orthogonalized image.…”

Section: Resultsmentioning

confidence: 99%

Bleed-Through Removal from Degraded Documents Using a Color Decorrelation Method

Tonazzini

Salerno

Mochi

et al. 2004

Document Analysis Systems VI

View full text Add to dashboard Cite

Abstract.A color decorrelation strategy to improve the human or automatic readability of degraded documents is presented. The particular degradation that is considered here is bleed-through, that is, a pattern that interferes with the text to be read due to seeping of ink from the reverse side of the document. A simplified linear model for this degradation is introduced to permit the application of very fast decorrelation techniques to the RGB components of the color data images, and to compare this strategy to the independent component analysis approach. Some examples from an extensive experimentation with real ancient documents are described, and the possibility to further improve the restoration performance by using hyperspectral/multispectral data is envisaged.

show abstract

Section: Resultsmentioning

confidence: 99%

Bleed-Through Removal from Degraded Documents Using a Color Decorrelation Method

Tonazzini

Salerno

Mochi

et al. 2004

Document Analysis Systems VI

View full text Add to dashboard Cite

show abstract

“…Thresholding approach is the most common procedure used in different applications, for example, in biomedical image analysis [41,42], handwritten character identification [43], automatic target recognition [44], change-detection applications [45–47], reconstruction of a map of interference fringes [48], and segmentation based on colour images [49]. Colour is one of the most significant low-level feature that can be used to extract homogeneous regions which are related to objects or part of objects most of the time, multilevel thresholding technique approaches [50,51], thresholding approach in Otsu algorithm [52], threshold approach in segmentation of satellite images [53], and other applications [15,54].…”

Section: Methodsmentioning

confidence: 99%

Application of automatic statistical post-processing method for analysis of ultrasonic and digital dermatoscopy images

Drulytė

Ruzgas

Raišutis

et al. 2018

Libyan Journal of Medicine

View full text Add to dashboard Cite

Ultrasonic and digital dermatoscopy diagnostic methods are used in order to estimate the changes of structure, as well as to non-invasively measure the changes of parameters of lesions of human tissue. These days, it is very actual to perform the quantitative analysis of medical data, which allows to achieve the reliable early-stage diagnosis of lesions and help to save more lives. The proposed automatic statistical post-processing method based on integration of ultrasonic and digital dermatoscopy measurements is intended to estimate the parameters of malignant tumours, measure spatial dimensions (e.g. thickness) and shape, and perform faster diagnostics by increasing the accuracy of tumours differentiation. It leads to optimization of time-consuming analysis procedures of medical images and could be used as a reliable decision support tool in the field of dermatology.

show abstract

“…In noise reduction alone there are hundreds of available techniques which can be categorized into three major groups of filtering, morphological operations and noise modeling [12] [13]. Filters can be designed for smoothing [14], sharpening [15], thresholding [16], removing slightly textured background [17] and contrast adjustment processes [18]. Various morphological operations can be designed to connect broken strokes [19], decompose the connected strokes [20], smooth the contours, prune the wild points, thin the characters [21], and extract boundaries [22].…”

Section: A Preprocessingmentioning

confidence: 99%

A Review on Feature Extraction and Feature Selection for Handwritten Character Recognition

Mohamad¹,

Hassan²,

Nasien³

et al. 2015

ijacsa

View full text Add to dashboard Cite

Abstract-The development of handwriting character recognition (HCR) is an interesting area in pattern recognition.HCR system consists of a number of stages which are preprocessing, feature extraction, classification and followed by the actual recognition. It is generally agreed that one of the main factors influencing performance in HCR is the selection of an appropriate set of features for representing input samples. This paper provides a review of these advances. In a HCR, the set of features plays as main issues, as procedure in choosing the relevant feature that yields minimum classification error. To overcome these issues and maximize classification performance, many techniques have been proposed for reducing the dimensionality of the feature space in which data have to be processed. These techniques, generally denoted as feature reduction, may be divided in two main categories, called feature extraction and feature selection. A large number of research papers and reports have already been published on this topic. In this paper we provide an overview of some of the methods and approach of feature extraction and selection. Throughout this paper, we apply the investigation and analyzation of feature extraction and selection approaches in order to obtain the current trend. Throughout this paper also, the review of metaheuristic harmony search algorithm (HSA) has provide.

show abstract

Integral ratio: a new class of global thresholding techniques for handwriting images

Cited by 107 publications

References 16 publications

Bleed-Through Removal from Degraded Documents Using a Color Decorrelation Method

Bleed-Through Removal from Degraded Documents Using a Color Decorrelation Method

Application of automatic statistical post-processing method for analysis of ultrasonic and digital dermatoscopy images

A Review on Feature Extraction and Feature Selection for Handwritten Character Recognition

Contact Info

Product

Resources

About