scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Adaptive method for multi colored text binarization

01 May 2017-pp 1-5
TL;DR: The main novelty of this reported work includes the calculation of each edge box based local color threshold value from CIELAB color space that makes the proposed system capable of binarizing multi colored texts where a single character has more than one color.
Abstract: This article presents our recent study on multi colored text binarization. In the output image, we represented foreground content as black and background as white regardless the polarity of foreground and background in original image. Here we applied connected component analysis based approach to group the words or characters within bounding or edge box. The main novelty of this reported work includes the calculation of each edge box based local color threshold value from CIELAB color space. This approach makes the proposed system capable of binarizing multi colored texts where a single character has more than one color. The proposed method has been executed on well-known D1BCO2009 and CMATERdb datasets that contain a large set of images to show the efficiency over other existing methods through qualitative comparison study.
Citations
More filters
Journal Article
TL;DR: This research work, the technique of genetic algorithm is applied which define the threshold value for the image binarization and it is analyzed that proposed algorithm performs well in terms of all parameters.
Abstract: A grey scale image is converted into black and white image through the binarization method. Binarization is a major factor on which the result of OCR depends. Within character recognition, higher accuracy is achieved by high quality binarized image in comparison to the original image which includes noise in it. Finding out an appropriate binarization algorithm for all the images is the major concern. Since there is huge difference in the performance of various binarization algorithms on different data sets, it is very difficult to choose the most optimal binarization algorithm. In this research work, the technique of genetic algorithm is applied which define the threshold value for the image binarization. The proposed algorithm is implemented in MATLAB and results are analyzed in terms of PSNR, MSE and Thinning rate. It is analyzed that proposed algorithm performs well in terms of all parameters.

Cites methods from "Adaptive method for multi colored t..."

  • ...The proposed technique works on every single pixel of the image [13]....

    [...]

References
More filters
Journal ArticleDOI
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Abstract: This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal assumptions about the form of the solution. We define detection and localization criteria for a class of edges, and present mathematical forms for these criteria as functionals on the operator impulse response. A third criterion is then added to ensure that the detector has only one response to a single edge. We use the criteria in numerical optimization to derive detectors for several common image features, including step edges. On specializing the analysis to step edges, we find that there is a natural uncertainty principle between detection and localization performance, which are the two main goals. With this principle we derive a single operator shape which is optimal at any scale. The optimal detector has a simple approximate implementation in which edges are marked at maxima in gradient magnitude of a Gaussian-smoothed image. We extend this simple detector using operators of several widths to cope with different signal-to-noise ratios in the image. We present a general method, called feature synthesis, for the fine-to-coarse integration of information from operators at different scales. Finally we show that step edge detector performance improves considerably as the operator point spread function is extended along the edge.

28,073 citations


"Adaptive method for multi colored t..." refers methods in this paper

  • ...In brief, Canny edge detection [8] is applied to group each text or character in individual edge box....

    [...]

  • ...[5] proposed Canny edge detection [8] based method to calculate the threshold after blurring the degraded document using Gaussian filter....

    [...]

  • ...Canny edge detection method [8] is one of those techniques which helps to track components in an image depending upon ρ....

    [...]

Journal ArticleDOI
TL;DR: A new method is presented for adaptive document image binarization, where the page is considered as a collection of subcomponents such as text, background and picture, which adapts and performs well in each case qualitatively and quantitatively.
Abstract: A new method is presented for adaptive document image binarization, where the page is considered as a collection of subcomponents such as text, background and picture. The problems caused by noise, illumination and many source type-related degradations are addressed. Two new algorithms are applied to determine a local threshold for each pixel. The performance evaluation of the algorithm utilizes test images with ground-truth, evaluation metrics for binarization of textual and synthetic images, and a weight-based ranking procedure for the "nal result presentation. The proposed algorithms were tested with images including di!erent types of document components and degradations. The results were compared with a number of known techniques in the literature. The benchmarking results show that the method adapts and performs well in each case qualitatively and quantitatively. ( 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

2,120 citations


"Adaptive method for multi colored t..." refers methods in this paper

  • ...Results out of the proposed method have been compared with other well known local binarization techniques, such as Sauvola’s method (SAUV) [3], Niblack’s method (NIBL) [2], Wolf et al....

    [...]

  • ...PSNR NRM MPM DRD SAUV [3] 86.37 16.33 10.61 0.63 6.59 NIBL [2] 26.51 4.54 36.94 193.69 134.05 WOL [7] 43.08 11.93 33.58 7.43 32.46 KASA [6] 57.26 12.01 24.65 10.48 32.56 Proposed method 92.35 18.82 4.12 0.61 3.23 Here some color text document images from DIBCO2009 [11], DIBCO2011 [12], DIBCO2013 [13], H-DIBCO2012 [14] and CMATERdb 6.1 [9] datasets and their corresponding binarized output images using the proposed method are shown in Fig....

    [...]

  • ...(c) Niblack’s method [2] (d) Sauvola’s method [3]...

    [...]

  • ...[3] reported a method that enhances the result of the previous method to remove such background noise....

    [...]

  • ...Results out of the proposed method have been compared with other well known local binarization techniques, such as Sauvola’s method (SAUV) [3], Niblack’s method (NIBL) [2], Wolf et al.’s method (WOL) [7], Bernsen’s method (BERN) [10], Gatos et al.’s method (GATO) [4], Biswas’s et al.’s method (BISW) [5], Kasar et al.’s method (KASA) [6]....

    [...]

Book
01 Jan 1986

1,745 citations


"Adaptive method for multi colored t..." refers background or methods in this paper

  • ...Results out of the proposed method have been compared with other well known local binarization techniques, such as Sauvola’s method (SAUV) [3], Niblack’s method (NIBL) [2], Wolf et al....

    [...]

  • ...PSNR NRM MPM DRD SAUV [3] 86.37 16.33 10.61 0.63 6.59 NIBL [2] 26.51 4.54 36.94 193.69 134.05 WOL [7] 43.08 11.93 33.58 7.43 32.46 KASA [6] 57.26 12.01 24.65 10.48 32.56 Proposed method 92.35 18.82 4.12 0.61 3.23 Here some color text document images from DIBCO2009 [11], DIBCO2011 [12], DIBCO2013 [13], H-DIBCO2012 [14] and CMATERdb 6.1 [9] datasets and their corresponding binarized output images using the proposed method are shown in Fig....

    [...]

  • ...(c) Niblack’s method [2] (d) Sauvola’s method [3]...

    [...]

  • ...Niblack [2] proposed a window based thresholding approach across the image....

    [...]

  • ...Results out of the proposed method have been compared with other well known local binarization techniques, such as Sauvola’s method (SAUV) [3], Niblack’s method (NIBL) [2], Wolf et al.’s method (WOL) [7], Bernsen’s method (BERN) [10], Gatos et al.’s method (GATO) [4], Biswas’s et al.’s method (BISW) [5], Kasar et al.’s method (KASA) [6]....

    [...]

01 Jan 1979

1,064 citations


"Adaptive method for multi colored t..." refers methods in this paper

  • ...Otsu's binarization method [1] is based on global thresholding and produces very good results for the document images in the absence of less variance among foreground and background and any degradation....

    [...]