scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Enhancement of inscription images

TL;DR: The proposed method improves word and character recognition accuracies of the OCR system by 65.3% and 54.3%, respectively, and is a suitable method for separating signals from a mixture of highly correlated signals.
Abstract: This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions neither possess standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast-ICA based analysis fail to extract text from these inscription images. Natural gradient Flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%) respectively.
Citations
More filters
Book ChapterDOI
01 Nov 2014
TL;DR: A novel interactive technique for extraction of text characters from the images of stone inscriptions is introduced in this paper, designed particularly for on-site processing of inscription images acquired at various historic palaces, monuments, and temples.
Abstract: A novel interactive technique for extraction of text characters from the images of stone inscriptions is introduced in this paper. It is designed particularly for on-site processing of inscription images acquired at various historic palaces, monuments, and temples. Its underlying principle is made of several robust character-analytic elements like HoG features, vowel diacritics, and location-bounded scan lines. Since the process involves character spotting and extraction of the inscribed information to editable text, it would subsequently help the archaeologists for epigraphy, transliteration, and translation of rock inscriptions, particularly for the ones having high degradations, noise, and a variety of styles according to the mason origin and reign. The spotted characters can also be used to create a database for ancient script analysis and related archaeological work. We have tested our method on various stone inscriptions collected from some of the heritage sites of Karnataka, India, and the results are quite promising. An Android application of the proposed work is also developed to aid the epigraphers in the study of inscriptions using a tablet or a mobile phone.

7 citations


Cites methods from "Enhancement of inscription images"

  • ...In [5], enhancement of inscription images for recognizing the text using OCR is performed using natural gradient based flexible ICA (NGFICA)....

    [...]

  • ...To identify the dating of a stone inscription by identifying its writer, other methodologies can be seen in [4, 5, 8, 9, 11]....

    [...]

Proceedings ArticleDOI
01 Feb 2018
TL;DR: This model consists phase congruency and of Gaussian model based background elimination using expectation maximization(EM) algorithm, preprocessing and binarization, which removes the background noise completely where foreground characters are untouched.
Abstract: Epigraphs are important sources for reshaping our culture and history. They have a remarkable importance to mankind. But modern epigraphists find it difficult to interpret the information in scripts. It is mainly because inscriptions are eroded over a period of time due to natural calamities. Scripts of ancient times are largely unknown. Character sets used have changed from one form to another over the centuries. Therefore, for reading ancient scripts the characters have to be extracted. In this paper, a model for enhancement and binarization of historical epigraphs is proposed. This model consists phase congruency and of Gaussian model based background elimination using expectation maximization(EM) algorithm, preprocessing and binarization. In binarization, phase based features are used with specialised filters. Adaptive Gaussian filters are used to smoothen the output images. Weighted mean angle is calculated to differentiate the foreground from the background. EM algorithm removes the background noise completely where foreground characters are untouched. Proposed method is tested on different datasets of inscriptions and epigraphs. Obtained results are compared with the existing classical algorithms.

4 citations


Cites methods from "Enhancement of inscription images"

  • ...In [3], author worked on the extraction of foreground object from the palm leaf using binarization method based on clustering traditional threshold computation....

    [...]

Book ChapterDOI
13 Sep 2017
TL;DR: A new approach for enhancement of Epigraphic Document images using Retinex method is presented in this paper, which enhances the visual clarity of the degraded images by highlighting the foreground text and suppressing the background noise.
Abstract: Epigraphic Documents are the ancient handwritten text documents inscribed on stone, metals, wood and shell. They are the most authentic, solitary and unique documented evidences available for the study of ancient history. In the recent years, Archeological Departments worldwide have taken up the massive initiative of converting their repository of ancient Epigraphic Documents into digital libraries for the perennial purpose of their preservation and easy dissemination. The visual quality of the digitized Epigraphic Document images is poor as they are captured from sources that would have suffered from various kinds of degradations like aging, depositions and risky handling. Enhancement of these images is an essential prerequisite to make them suitable for automatic character recognition and machine translation. A new approach for enhancement of Epigraphic Document images using Retinex method is presented in this paper. This method enhances the visual clarity of the degraded images by highlighting the foreground text and suppressing the background noise. The method has been tested on digitized estampages of ancient stone inscriptions of 11th century written in old Kannada language. The results achieved are efficient in terms of root mean square contrast and standard deviation.

4 citations

Proceedings ArticleDOI
26 Aug 2022
TL;DR: This survey attempts to give a detailed analysis of the recent research works on character recognition from the images of stone inscriptions with a special reference to Tamil, and details the methods applied for preprocessing, feature extraction and classification.
Abstract: Character recognition on inscriptions is an area which explores our knowledge of an ancient language. Inscriptions were done in all kinds of environments. This work focuses on recognizing Tamil language characters on stone-based images. From the inscription images, we come to know about the importance of old century languages. Some of the general challenges researchers face in recognizing the characters in stone inscriptions are differentiating the foreground pixel from the background stone images, perspective distortion, different light illumination, the same kind of background/foreground, damaged stones, lack of shape and size of the text. Despite the different ways proposed by the researchers, obstacles and issues continue to exist. This survey attempts to give a detailed analysis of the recent research works on character recognition from the images of stone inscriptions with a special reference to Tamil. It details the methods applied for preprocessing, feature extraction and classification. It gives a road map for future researchers who wish to carry out research in this area.

2 citations

Proceedings ArticleDOI
08 Sep 2014
TL;DR: The proposed work describes the difficulties during the conversion of inscription digitization, preservation and trifling dissimilarities among forefront and background and proposes methodology that enhances the words and recognizes the characters alone.
Abstract: The proposed work describes the difficulties during the conversion of inscription digitization, preservation and trifling dissimilarities among forefront and background. Basically the inscriptions were neither retained traditional size and nor the shape. Even though they doesn't have colour discrepancy linking foreground and background. In priviling technique describes the extractions in the inscription by using NGFICA method. Our method enhances the words and recognizes the characters alone. In proposing methodology the inscription that has been enhanced, recognized effortlessly.

2 citations

References
More filters
Journal ArticleDOI
TL;DR: The main result of this paper are analytic closed-form expressions that characterize the separating ability of both versions of the FastICA algorithm in a local sense, assuming a "good" initialization of the algorithms and long data records.
Abstract: The FastICA or fixed-point algorithm is one of the most successful algorithms for linear independent component analysis (ICA) in terms of accuracy and computational complexity. Two versions of the algorithm are available in literature and software: a one-unit (deflation) algorithm and a symmetric algorithm. The main result of this paper are analytic closed-form expressions that characterize the separating ability of both versions of the algorithm in a local sense, assuming a "good" initialization of the algorithms and long data records. Based on the analysis, it is possible to combine the advantages of the symmetric and one-unit version algorithms and predict their performance. To validate the analysis, a simple check of saddle points of the cost function is proposed that allows to find a global minimum of the cost function in almost 100% simulation runs. Second, the Crame/spl acute/r-Rao lower bound for linear ICA is derived as an algorithm independent limit of the achievable separation quality. The FastICA algorithm is shown to approach this limit in certain scenarios. Extensive computer simulations supporting the theoretical findings are included.

166 citations


"Enhancement of inscription images" refers background in this paper

  • ...More recently, its convergence has been shown to slow down or even fail in the presence of saddle points, particularly for short block sizes [11]....

    [...]

Proceedings ArticleDOI
22 Jun 1999
TL;DR: This work describes a method for detection and representation of text in video segments that can be applied to English as well as non-English text (such as Korean) with precision and recall of 85%.
Abstract: Textual information brings important semantic clues in video content analysis. We describe a method for detection and representation of text in video segments. The method consists of seven steps: channel separation, image enhancement, edge detection, edge filtering, character detection, text box detection, and text line detection. Our results show that this method can be applied to English as well as non-English text (such as Korean) with precision and recall of 85%.

116 citations

Proceedings ArticleDOI
23 Aug 2004
TL;DR: The proposed method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature confirmed that extraction rates are high even in complex images.
Abstract: We propose a method that extracts text regions in natural scene images using low-level image features and that verifies the extracted regions through a high-level text stroke feature. Then the two level features are combined hierarchically. The low-level features are color continuity, gray-level variation and color variance. The color continuity is used since most of the characters in a text region have the same color, and the gray-level variation is used since the text strokes are distinctive to the background in their gray-level values. Also, the color variance is used since the text strokes are distinctive in their colors to the background, and this value is more sensitive than the gray-level variations. As a high level feature, text stroke is examined using multi-resolution wavelet transforms on local image areas and the feature vector is input to a SVM (support vector machine) for verification. We tested the proposed method with various kinds of the natural scene images and confirmed that extraction rates are high even in complex images.

104 citations


"Enhancement of inscription images" refers methods in this paper

  • ...[7] used 64 clustered color channels for text detection where cluster colors are based on Euclidean distance in the RGB space....

    [...]

Proceedings ArticleDOI
10 Dec 2002
TL;DR: This work uses multiple frame verification to reduce text detection false alarms and applies a block-based adaptive thresholding procedure to form a clearer "man-made" frame that is sent to an OCR engine for recognition.
Abstract: Text superimposed on the video frames provides supplemental but important information for video indexing and retrieval. Many efforts have been made for videotext detection and recognition (video OCR). The main difficulties of video OCR are the low resolution and the background complexity. We present efficient schemes to deal with the second difficulty by sufficiently utilizing multiple frames that contain the same text to get every clear word from these frames. Firstly, we use multiple frame verification to reduce text detection false alarms. We then choose those frames where the text is most likely clear, thus it is more possible to be correctly recognized. We then detect and joint every clear text block from those frames to form a clearer "man-made" frame. Later we apply a block-based adaptive thresholding procedure on these "man-made" frames. Finally, the binarized frames are sent to an OCR engine for recognition. Experiments show that the word recognition rate has been increased over 28% by these methods.

77 citations


"Enhancement of inscription images" refers background in this paper

  • ...In [6], the "uniform color" blocks within the high contrast video frames are selected to correctly extract text regions....

    [...]

  • ...color and there is low contrast between text and background thus making the use of [6] unsuitable....

    [...]

Proceedings ArticleDOI
01 Dec 2008
TL;DR: An Independent Component Analysis (ICA)-based image enhancement technique is presented to improve the accuracy for machine reading of camera-based images and shows the potential of the proposed ICA-based method.
Abstract: An Independent Component Analysis (ICA)-based image enhancement technique is presented to improve the accuracy for machine reading of camera-based images. Images of inscriptions that are normally engraved on stones or other durable materials and found at the sites of historical monuments are taken as a reference for conducting the present experiments. Significant improvement in recognition rate of a commercial OCR system shows the potential of the proposed ICA-based method. It improves word and character recognition accuracies of the OCR system by 68.6% (from 11.2% to 79.8%) and 57.3% (from 34.8% to 92.1%), respectively.

21 citations


"Enhancement of inscription images" refers background or methods in this paper

  • ...Garain et al [3] describe how to enhance image using Fas­...

    [...]

  • ...FastlCA [3] based enhancement method has given good results for inscription...

    [...]

  • ...We have also compared the proposed method with Fast ICA based enhancement [3] and results are shown in...

    [...]