A modified K3M thinning algorithm

Tabędzki, Marek; Saeed, Khalid; Szczepański, Adam

doi:10.1515/amcs-2016-0031

Cited by 19 publications

(11 citation statements)

References 16 publications

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“…• In the next step, the image is converted into a binary representation and friction ridges are thinned by the algorithm of Pavlidis (1982) or Tabedzki et al (2016). In our paper we employ Pavlidis's method.…”

Section: Proposed Method: the General Ideamentioning

confidence: 99%

An accurate fingerprint reference point determination method based on curvature estimation of separated ridges

Doroz

Wróbel

Porwik

2018

International Journal of Applied Mathematics and Computer Science

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This paper presents an effective method for the detection of a fingerprint’s reference point by analyzing fingerprint ridges’ curvatures. The proposed approach is a multi-stage system. The first step extracts the fingerprint ridges from an image and transforms them into chains of discrete points. In the second step, the obtained chains of points are processed by a dedicated algorithm to detect corners and other points of highest curvature on their planar surface. In a series of experiments we demonstrate that the proposed method based on this algorithm allows effective determination of fingerprint reference points. Furthermore, the proposed method is relatively simple and achieves better results when compared with the approaches known from the literature. The reference point detection experiments were conducted using publicly available fingerprint databases FVC2000, FVC2002, FVC2004 and NIST

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Section: Proposed Method: the General Ideamentioning

confidence: 99%

An accurate fingerprint reference point determination method based on curvature estimation of separated ridges

Doroz

Wróbel

Porwik

2018

International Journal of Applied Mathematics and Computer Science

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“…This algorithm was selected to prepare finger veins to feature extraction. During the experimental phase we tested different algorithms as Zhang [20], KMM [21], K3M [22] and morphological hit-or-miss operator [23]. On the basis of all observations, it has to be claimed that the K3M algorithm provided the best, most precise results.…”

Section: Image Processing For Finger Veins Feature Extractionmentioning

confidence: 99%

Raspberry Pi-Based Device for Finger Veins Collection and the Image Processing-Based Method for Minutiae Extraction

Szymkowski

2021

Computer Information Systems and Industrial Management

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Biometrics is one of the most important ways to secure users' data. It gained popularity due to effectiveness and ease of usage. It was proven that diversified solutions based on measurable traits can guarantee higher security levels than traditional authentication-based (logins and passwords). The most popular are fingerprint and iris (especially in mobile devices). In this work we would like to present our own algorithm connected with finger veins features extraction. At the beginning all details of the device for samples collection are given. In the further part significant information related to finger veins extraction are described in the details. Image processing methods were used to show that even with traditional, well-known algorithms it is possible to obtain precise information about human veins. The final step in our algorithm is connected with feature vector generation. In this work we do not present a classification stage as it is out of its scope.

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“…As shown in Figure 3, all lines in the image are narrowed until they reach a width of 1 pixel. The modified K3M algorithm used in this publication has been created by one of the authors [10].…”

Section: Modified K3m Algorithmmentioning

confidence: 99%

Hiragana and Katakana Minutiae based Recognition System

Szymkowski¹,

Saeed²,

Nishiuchi³

2021

Adv. sci. technol. eng. syst. j.

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The Japanese writing system is unique due to the number of characters employed and the methods used to write words. It consists of three different 'alphabets', which may result in the methods used to process Latin script not being sufficient to obtain satisfactory results when attempting to apply them to a recognition of the Japanese script. The authors present an algorithm based on minutiae, i.e., feature points, to recognise the hiragana and katakana characters. A method using image processing algorithms is compared with a method using a neural network for the purpose of automating this process. Based on the distribution and type of minutiae, vectors of features have been created to recognise 96 different characters. The authors conducted a study showing the effect of the chosen segmentation method on the accuracy of the character recognition. The proposed solution has achieved a maximum accuracy at the level of 65.2%.

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A modified K3M thinning algorithm

Cited by 19 publications

References 16 publications

An accurate fingerprint reference point determination method based on curvature estimation of separated ridges

An accurate fingerprint reference point determination method based on curvature estimation of separated ridges

Raspberry Pi-Based Device for Finger Veins Collection and the Image Processing-Based Method for Minutiae Extraction

Hiragana and Katakana Minutiae based Recognition System

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