Detecting fingerprint minutiae by run length encoding scheme

Shin, Jung Hye; Hwang, Hui-Yeoun; Chien, Sung‐Il

doi:10.1016/j.patcog.2005.12.013

Cited by 21 publications

(7 citation statements)

References 23 publications

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“…This characteristic makes it become widely used [11,13,14,15,17] and even become a component of other schemes, such as the JPEG standard [10], proposed in 1980's and in use for transmitting and storing images, uses discrete cosine transformation, quantization, run-length coding, and Huffman entropy coding [2]. The idea of run-length encoding has also been extensively exploited by researchers for other kinds of data compression.…”

Section: Related Workmentioning

confidence: 99%

An Improved Run Length Encoding Scheme for Image Compression

Samson¹,

Sastry²

2017

IJECS

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Abstract:In this paper, we propose an Improved Run-Length Encoding (IRLE) scheme for image compression. Conventional RunLength Encoding is a widely used scheme as it is simple and effective but not suitable to represent non-block images. The IRLE which we have developed, combines runs and run values and it reduces the space required to store the image significantly. The compression ratio depends on the size and type of the input message. From the results obtained in this analysis, we conclude that the proposed approach is an efficient method for image compression and it provides high compression ratio and better compression percentage.

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Section: Related Workmentioning

confidence: 99%

An Improved Run Length Encoding Scheme for Image Compression

Samson¹,

Sastry²

2017

IJECS

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“…By using a RLE algorithm for every line in Era, defects will be found and labeled. RLE is a simple and popular encoding algorithm [14] . It is implemented by the following object-oriented-programming (OOP) based method in our approach.…”

Section: Fast Defects Searching By Run-length-encoding (Rle)mentioning

confidence: 99%

High speed web printing inspection with multiple linear cameras

Shi

2011

MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications

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Purpose: To detect the defects during the high speed process of web printing, such as smudges, doctor streaks, pin holes, character misprints, foreign matters, hazing, wrinkles, etc., which are the main infecting factors to the quality of printing presswork. Methods: A set of novel machine vision system is used to detect the defects. This system consists of distributed data processing with multiple linear cameras, effective anti-blooming illumination design and fast image processing algorithm with blob searching. Also, pattern matching adapted to paper tension and snake-moving are emphasized. Results: Experimental results verify the speed, reliability and accuracy of the proposed system, by which most of the main defects are inspected at real time under the speed of 300 m/min. Conclusions: High speed quality inspection of large-size web requires multiple linear cameras to construct distributed data processing system. Also material characters of the printings should also be stressed to design proper optical structure, so that tiny web defects can be inspected with variably angles of illumination.

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“…In [5] a run length coding based method for bifurcation and endpoint detection, which does not require thinning, is presented. The run length coding requires that the input image is binary and it is performed in two dimensions, thus allowing for the detection of starting, ending, merging, and splitting runs.…”

Section: B Feature Detectionmentioning

confidence: 99%

Convolution approach for feature detection in topological skeletons obtained from vascular patterns

Olsen

Hartung²,

Busch

et al. 2011

2011 IEEE Workshop on Computational Intelligence in Biometrics and Identity Management (CIBIM)

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Abstract-In image processing connected structures can be reduced to an abstract binary skeleton. These skeletons are 1-pixel wide structures which retain the topology of the segmented image. They are used for computer vision, edge detection or high level feature extraction for example in biometric systems. In this paper a fast method on how to extract specific feature points from skeletonized structures is presented. The convolution of the skeleton image with a bi-dimensional mask of size MxN enables us to identify arbitrary structures of the mask size in the skeleton. Of special interest are branch and endpoints of the skeletons to get high level features for biometric comparisons. The problem can here be reduced to the following: in an 8-connected skeleton within a 3x3 mask there are 8 structures that correspond to endpoints and 18 to branch points. After applying the convolution, the search for feature points corresponds to finding the 26 different filter response values in the resulting signal. We describe how the convolution approach is applied to biometric vein recognition systems and show that our approach yields a 430% speedup when compared to the crossing number approach used in ANSI/NIST.

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Detecting fingerprint minutiae by run length encoding scheme

Cited by 21 publications

References 23 publications

An Improved Run Length Encoding Scheme for Image Compression

An Improved Run Length Encoding Scheme for Image Compression

High speed web printing inspection with multiple linear cameras

Convolution approach for feature detection in topological skeletons obtained from vascular patterns

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