Robust Feature Extraction Technique for Optical Character Recognition

Ramanathan, R.; Nair, Arun Sukumaran; Thaneshwaran, L.; Ponmathavan, S.; Valliappan, Nachiappan

doi:10.1109/act.2009.145

Cited by 19 publications

(4 citation statements)

References 6 publications

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“…Here a 2D Gabor filter has been used for the purpose of feature extraction. A 2D Gabor is a Gaussian modulated sinusoid in the spatial domain and a shifted as a shifted Gaussian in the frequency domain [23]. It is represented by equations (2) and (3), it can also be shown in figure 8.a and 8.b.…”

Section: Fourier Transformmentioning

confidence: 99%

Feature Extraction Techniques for Text Recognition of Indian Scripts

Sinha¹

2019

IJRASET

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Several research works has been done by many researchers on Optical Character Recognition system. But various work has been done is on Greek, Chinese, English and Japanese characters. There has not been sufficient quality of work on text recognition of Indian languages like Bangla, Marathi, Malayalam, Telugu, Gujarati, Kannada, Gurumukhi and Oriya. The development of handwritten text recognition (HTR) is an interesting area in pattern recognition. In HTR, the set of features are very important in selecting the appropriate feature that produces little classification error. In this paper, we have presented a study on feature extraction and classification techniques used for character recognition of Indian scripts. In the fast moving world with the amazingly expanding technology, character recognitions play a ample role by providing more scope to perform research in OCR techniques.A considerable advancement in the work associated with the recognition of handwritten and printed text has been reported in last few years. From the last few decades offline handwritten text recognition has gained a lot of interest of researchers. It is well known that each individual people have some different writing style, so it is very difficult to identify or recognize the handwritten characters or numerals. Based on data gathering process a concise classification of recognition system has been discussed in this paper. Several feature extraction techniques & classifiers like, diagonal feature extraction, transition feature extraction, K-NN classifier (K-nearest neighbour) & SVM classifier (Support vector machine) are also illustrated in this paper. The methodology for word recognition has also been briefly explained in this paper.

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Section: Fourier Transformmentioning

confidence: 99%

Feature Extraction Techniques for Text Recognition of Indian Scripts

Sinha¹

2019

IJRASET

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“…Due to the different nature of different scripts, the different segmentation mechanism is required for different languages [22]. And Feature extraction is a key step in the process of OCR, which in fact is a deciding factor of the accuracy of the system [23] and can efficient with the use of suitable approach depending on the nature of characters.…”

Section: Introductionmentioning

confidence: 99%

OCRMPD: OCR system for Myanmar printed document image with a novel segmentation method and hierarchical classification scheme

Win

Khine

Tun

2011

2011 IEEE 7th International Conference on Intelligent Computer Communication and Processing

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As large quantity of document images is getting archived by the digital libraries, an efficient strategy that can convert Myanmar document image into machine understandable text format is needed. And Myanmar language contains many words, and most of them are similar, especially for small fonts, the accuracy of the Optical Character Recognition, OCR system for Myanmar may be low. Therefore, this paper designs an OCR system for Myanmar Printed Document (OCRMPD) with several proposed methods that can automatically convert Myanmar printed text to machine understandable text. In order to get more accurate system, enhance the input image by removing noise and making some correction on variants. A method for isolation of the character image is proposed by using connected component analysis for wrongly segmented characters produced by projection only. Finally, hierarchical mechanism is used for SVM classifier for recognition of the character image. The proposed algorithms have been tested on a variety of Myanmar printed documents and the results of the experiments indicate that the methods can increase the segmentation accuracy as well as recognition rates.

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“…Optical character recognition GFs are utilized for text segmentation [28], character recognition [46], font recognition [25], and license plate recognition [5].…”

Section: Introduction and Related Workmentioning

confidence: 99%

Curved Gabor Filters for Fingerprint Image Enhancement

Gottschlich

2011

Preprint

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Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters 1 which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods.

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Robust Feature Extraction Technique for Optical Character Recognition

Cited by 19 publications

References 6 publications

Feature Extraction Techniques for Text Recognition of Indian Scripts

Feature Extraction Techniques for Text Recognition of Indian Scripts

OCRMPD: OCR system for Myanmar printed document image with a novel segmentation method and hierarchical classification scheme

Curved Gabor Filters for Fingerprint Image Enhancement

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