Some new heuristics for thinning binary handprinted characters for OCR

Stentiford, Fred; Mortimer, Rudolf G.

doi:10.1109/tsmc.1983.6313034

Cited by 59 publications

(26 citation statements)

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“…Amongst many thinning algorithms such as Holt and Stewart [20], Stentiford [21], Zhang-Suen [22], the experimental results show that Hilditch algorithm [23] is simple algorithm and gives better answer with the fingerprint image. The selected algorithm is described as following: At point P1 on the ridge, consider the 8-neighbors of pixel P1.Then, calculate A(P1) and B(P1) where A(P1) is the number of pairs (0, 1) in the sequence P2, P3, P4, P5, P6, P7, P8, P9, P2 and B(P1) is the number of neighbor pixels whose values are not zero.…”

Section: Binary Imagementioning

confidence: 99%

A robust fingerprint watermark-based authentication scheme in H.264/AVC video

Nguyen

Tran

2014

Vietnam J Comput Sci

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In this paper, we propose a novel technique that uses fingerprint features with coordinates (x, y), angle and type of feature as watermark information for authentication in H.264/AVC video. We utilize some techniques such as Gabor algorithm, locally adaptive thresholding, and Hilditch's thinning together with heuristic rules and Hamming measurement to optimally extract minutiae vector (x, y, angle, type) from fingerprint as well as to improve accuracy of matching process. Furthermore, to make our scheme robust, the minutiae vector will be converted to binary stream which is increased three times and the lowest frequency of DCT blocks of transition images or frames in H.264 video is properly chosen to hold them. With our proposed technique, the authentication scheme can achieve high capacity and good quality. Experimental results show that our proposed technique is robust against to H.264 encoder, time stretching in video, Gaussian noise, adding blur, frame removal in video, and cutting some regions in the frame of video.

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Section: Binary Imagementioning

confidence: 99%

A robust fingerprint watermark-based authentication scheme in H.264/AVC video

Nguyen

Tran

2014

Vietnam J Comput Sci

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“…5) Алгоритм Стентіфорда, що відноситься до ітераційних алгоритмів з послідовним застосуван-ням 4-х витончуючих шаблонів розміром 3*3 піксе-ля [25].…”

Section: етапи покадрової обробки відеопотоку в си-стеміunclassified

Construction principles of computer systems for remote training based on the analysis of the video stream

Нгуєн¹,

Болтьонков²,

Малявін³

2014

EEJET

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“…In this work the Stentiford thinning method [8] is used. Fig.1(d) shows the skeletonization results.…”

Section: Feature Point Detectionmentioning

confidence: 99%

Characterisation of Feature Points in Eye Fundus Images

Calvo

Penedo

Rouco

2009

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Abstract. The retinal vessel tree adds decisive knowledge in the diagnosis of numerous opthalmologic pathologies such as hypertension or diabetes. One of the problems in the analysis of the retinal vessel tree is the lack of information in terms of vessels depth as the image acquisition usually leads to a 2D image. This situation provokes a scenario where two different vessels coinciding in a point could be interpreted as a vessel forking into a bifurcation. That is why, for traking and labelling the retinal vascular tree, bifurcations and crossovers of vessels are considered feature points. In this work a novel method for these retinal vessel tree feature points detection and classification is introduced. The method applies image techniques such as filters or thinning to obtain the adequate structure to detect the points and sets a classification of these points studying its environment. The methodology is tested using a standard database and the results show high classification capabilities.

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Some new heuristics for thinning binary handprinted characters for OCR

Cited by 59 publications

References 0 publications

A robust fingerprint watermark-based authentication scheme in H.264/AVC video

A robust fingerprint watermark-based authentication scheme in H.264/AVC video

Construction principles of computer systems for remote training based on the analysis of the video stream

Characterisation of Feature Points in Eye Fundus Images

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