Text region extraction from low resolution natural scene images using texture features

Angadi, S. A.; Kodabagi, M. M.

doi:10.1109/iadcc.2010.5423026

Cited by 30 publications

(12 citation statements)

References 17 publications

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“…proposed an algorithm for texture features based on discrete cosine transform (DCT). The method is applied on 100 natural scene images, it is inefficient when image background is more complex like trees, vehicles [10]. In 2010 Epshtein et al proposed a method to detect texts in many languages with different fonts based on stroke width transform (SWT) [11].…”

Section: Related Workmentioning

confidence: 99%

Wavelet transform based technique for text image localization

Ali

Hashim

2016

Karbala International Journal of Modern Science

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In this paper, a robust technique based on discrete wavelet transform, edge detection, and morphology operation for scene text detection is proposed. There are several stages in the proposed method. In the first stage, a single wavelet decomposition LH, HL and HH subbands are applied for detecting edges in original scene text image. The projection technique is applied in the second stage to preliminary detect text and non-text pixels. In third stage, 4-connected components are applied, and then area geometric feature is used as threshold to remove non-text region. At last stage, morphological operations are applied to connect isolated text components and to remove non-text regions. The proposed method is applied on a various images such as images of low contrast, complex background images and images of different fonts and size of text. The experimental results show that the proposed method can detect regions of the text perfectly.

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Section: Related Workmentioning

confidence: 99%

Wavelet transform based technique for text image localization

Ali

Hashim

2016

Karbala International Journal of Modern Science

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“…Secondly, supported on the output of SFT they are appropriate two classifiers a text part classifier and a text-line classifier successively to remove text areas. [15], proposed a method for 'Text Region Extraction from Low Resolution Natural Scene Images using Texture Features'. It is texture based and functions on low resolution natural scene images incarcerated by cameras implanted in mobile phones to detect and segment text areas.…”

Section: Literature Surveymentioning

confidence: 99%

Untitled

2016

IJDPS

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Scene text recognition brings various new challenges occurs in recent years. Detecting and recognizing text in scenes entails some of the equivalent problems as document processing, but there are also numerous novel problems to face for recognizing text in natural scene images. Recent research in these regions has exposed several promise but present is motionless much effort to be entire in these regions. Most existing techniques have focused on detecting horizontal or near-horizontal texts. In this paper, we propose a new scheme which detects texts of arbitrary directions in natural scene images. Our algorithm is equipped with two sets of characteristics specially designed for capturing both the natural characteristics of texts using MSER regions using Otsu method. To better estimate our algorithm and compare it with other existing algorithms, we are using existing MSRA Dataset, ICDAR Dataset, and our new dataset, which includes various texts in various real-world situations. Experiments results on these standard datasets and the proposed dataset shows that our algorithm compares positively with the modern algorithms when using horizontal texts and accomplishes significantly improved performance on texts of random orientations in composite natural scenes images.

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“…On the other hand, texture-based methods are implemented based on the observation that texts in images have distinct textural properties that distinguish them from the background [21,22]. The methods scan the image and classify the pixel neighbourhoods based on a number of text properties such as density of edges, gradients, variance of intensity and distribution of wavelet.…”

Section: Previous Workmentioning

confidence: 99%

Extraction of arbitrary text in natural scene image based on stroke width transform

Jameson¹,

Abdullah

2014

2014 14th International Conference on Intelligent Systems Design and Applications

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Text extraction plays an important role in numerous applications. Research on its method still need to be improved in order to achieve better performance, to increase the reliability of text extraction system and to deal with complex cases of text extraction. The maj ority of the text extraction methods are focusing on horizontal and near horizontal text lines; however, text in natural scene might be in arbitrary line in real time. Thus, this paper aims to solve the issue of extracting the arbitrary oriented text by suggesting a method for text detection and localization based on the Stroke Width Transform. The proposed method is tested on an arbitrary text dataset and ICDAR dataset. The result of the experiment shows that the proposed method adapts well to the arbitrary text.

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Text region extraction from low resolution natural scene images using texture features

Cited by 30 publications

References 17 publications

Wavelet transform based technique for text image localization

Wavelet transform based technique for text image localization

Untitled

Extraction of arbitrary text in natural scene image based on stroke width transform

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