Thresholding Algorithm for Local and Parallel Processing

Iwakata, Satohi; Ajioka, Yoshiaki; Hagiwara, Masafumi

doi:10.1541/ieejeiss.125.7

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…For the thresholding of a single input image, a method has been proposed to set the threshold at a target position using the minimum value in the neighborhood after smoothing and edge extraction . The method has produced good thresholding results for characters on street signs.…”

Section: Introductionmentioning

confidence: 99%

Image Thresholding by Improved Convergent Floating Thresholding Method Using Extended Control Value

Ueno

Yamaguchi

2013

Elect Comm in Japan

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SUMMARY In this paper, the authors propose a threshold setting method for binary images. This method consists of two steps which are different threshold calculating algorithms. The first step is an improved model of the Convergent Floating Thresholding Method, with switching between two control values to update a tentative threshold. By this step, thresholding of a boundary area of gray level change is performed. The second step is composed of the discriminant analysis method and is applied to flat areas of gray level. A feature of the proposed method is comparison of the gray level with two final tentative thresholds which are obtained using two coefficients as control values. With this method, it is possible to decrease thresholding error which occurs in the case of low contrast and brightness change. Pattern in similar gray‐level areas can also be clarified. The proposed method and the conventional methods were tested, using general outdoor scene images. The results showed that the proposed method can output good‐quality binary images and is useful for thresholding of scene images. © 2013 Wiley Periodicals, Inc. Electron Comm Jpn, 97(1): 82–88, 2014; Published online in Wiley Online Library (http://wileyonlinelibrary.com). DOI 10.1002/ecj.11495

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Section: Introductionmentioning

confidence: 99%

Image Thresholding by Improved Convergent Floating Thresholding Method Using Extended Control Value

Ueno

Yamaguchi

2013

Elect Comm in Japan

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Pictogram Extraction Algorithm for Local and Parallel Processing

Iwakata

Fujita

Ajioka³

et al. 2006

IEEJ Trans.EIS

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Keywords: image processing, pictogram extraction, scenery image, local and parallel image processing, support for sight-restricted peopleIn this paper, we propose a pictogram extraction algorithm for local and parallel processing. Then, we show the example that the proposed algrithm is applied to lavatory mark detection. This algorithm works under a severe constraint: each pixel of a result image must be derived from only information of their neighbor pixels. This constraint is very important for a low cost device like a mobile camera because many other algorithms using grobal process can not be really carried out in such a device. Fig. 1 shows our target device. It consists of many Processing Elements (PE). This device can process images in parallel due to independency of PEs.The proposed algorithm can estimate degree of square by pixel count method to extract pictograms. Fig. 2 shows the flow of the proposed algorithm. Fig. 3 shows examples of computer simulations. The result shows that the proposed algorithm can extract pictogram regions in a rate of more than 90%, and false detection rate is less than 20%.

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Convergent Floating Thresholding for Image Extraction

Yamaguchi¹,

Kunishi²

2009

IEEJ Trans.EIS

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Thresholding Algorithm for Local and Parallel Processing

Cited by 4 publications

References 6 publications

Image Thresholding by Improved Convergent Floating Thresholding Method Using Extended Control Value

Image Thresholding by Improved Convergent Floating Thresholding Method Using Extended Control Value

Pictogram Extraction Algorithm for Local and Parallel Processing

Convergent Floating Thresholding for Image Extraction

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