With the increasing popularity of digital cameras attached with various handheld devices, many new computational challenges have gained significance. One such problem is extraction of texts from natural scene images c...
详细信息
With the increasing popularity of digital cameras attached with various handheld devices, many new computational challenges have gained significance. One such problem is extraction of texts from natural scene images captured by such devices. The extracted text can be sent to OCR or to a text-to-speech engine for recognition. In this article, we propose a novel and effective scheme based on analysis of connected components for extraction of Devanagari and Bangla texts from camera captured scene images. A common unique feature of these two scripts is the presence of headline and the proposed scheme uses mathematical morphology operations for their extraction. Additionally, we consider a few criteria for robust filtering of text components from such scene images. Moreover, we studied the problem of binarization of such scene images and observed that there are situations when repeated binarization by a well-known global thresholding approach is effective. We tested our algorithm on a repository of 100 scene images containing texts of Devanagari and / or Bangla.
Answering to a query like when a particular document was printed is quite helpful in practice especially forensic purposes. This study attempts to develop a general framework that makes use of image processing and pat...
详细信息
Writer identification is a vibrant research field, though a lot of work has been done on writer identification on normal text, writer identification in music score sheet has not been addressed in that large scale. Her...
详细信息
ISBN:
(纸本)9781479925735
Writer identification is a vibrant research field, though a lot of work has been done on writer identification on normal text, writer identification in music score sheet has not been addressed in that large scale. Here we propose a method to identify writers of music score sheets using Daubchies wavelet features along with SVM classifier. We have evaluated our proposed approach in a sub-set of CVC-MUSCIMA dataset. From the experiment on 140 score sheet images from 7 writers we obtained encouraging results.
In a multi-lingual country like India, a document may contain more than one script forms. For such a document it is necessary to separate different script forms before feeding them to OCRs of individual script. In thi...
详细信息
In a multi-lingual country like India, a document may contain more than one script forms. For such a document it is necessary to separate different script forms before feeding them to OCRs of individual script. In this paper an automatic word segmentation approach is described which can separate Roman, Bangla and Devnagari scripts present in a single document. The approach has a tree structure where at first Roman script words are separated using the 'headline' feature. The headline is common in Bangla and Devnagari but absent in Roman. Next, Bangla and Devnagari words are separated using some finer characteristics of the character set although recognition of individual character is avoided. At present, the system has an overall accuracy of 96.09%.
Core region detection of handwritten cursive words is an important step towards their automatic recognition. Several preprocessing operations such as height normalization, slant estimation etc. Are often based on this...
详细信息
Core region detection of handwritten cursive words is an important step towards their automatic recognition. Several preprocessing operations such as height normalization, slant estimation etc. Are often based on this core region. This is particularly useful for word recognition of major indian scripts, which have large character sets. The main parts of majority of these characters belong to the core region that is bounded above by a headline and bounded below by an imaginary base line. Only a few such characters or their parts appear either above or below the core region. A few approaches are available in the literature for detection of such a core region of offline handwritten word samples of Latin script. Also, a similar region is often determined for recognition of images of printed indian scripts. However, none of these approaches have studied detection of core region of an unconstrained online handwritten word. In this article, we propose a novel method for detection of the core region of online handwritten word samples of Bangla, a major indian script. For this we first perform smoothing on the samples and then segment a stroke into sub strokes. We compute certain novel positional features from each such sub stroke. Using these features, a multilayer perceptron (MLP) is trained by back propagation (BP) algorithm. On the basis of the output of the MLP, we determine the position of both the headline and the baseline. We have tested this approach on a recently developed large database of online unconstrained handwriting Bangla word samples. The proposed approach would also work on similar samples of Devanagari, another major indian script. Experimental results are encouraging.
This paper deals with segmentation and recognition of touching characters appearing in scanned mathematical expressions. The technique is based on multifactorial analysis that integrates several factors determining cu...
详细信息
This paper deals with segmentation and recognition of touching characters appearing in scanned mathematical expressions. The technique is based on multifactorial analysis that integrates several factors determining cut-positions in a touching character image. A predictive algorithm is developed for efficient selection of possible cut-positions for segmenting touching characters. Experiment has been carried out using a test-set of reasonable size and results show that a considerable improvement in recognition accuracy can be achieved with a modest increase in computations.
Water causes degradation of quality in optical images captured underwater due to its physical properties of absorption and scattering. This degradation is further aggravated by the increase in water depth and the pres...
详细信息
ISBN:
(数字)9798350359312
ISBN:
(纸本)9798350359329
Water causes degradation of quality in optical images captured underwater due to its physical properties of absorption and scattering. This degradation is further aggravated by the increase in water depth and the presence of contaminated water. Transformers in the vision domain have made a quantum leap in many vision tasks such as detection, and segmentation but yet to make any progress in enhancing degraded underwater images. We propose a transformer-based model named “Aquaformer” which makes four major contributions: an adaptive layer normalization, replacement of masked cyclic shift with symmetric padding in window partitioning, a novel aggregation mechanism, and an adjustable fusion approach. These succeed in making the model a very powerful one, producing significantly better performance compared to the latest state-of-the-art methods. Testing on multiple benchmark datasets, employing both quantitative and qualitative metrics, establishes its supremacy.
This paper deals with an OCR error detection and correction technique for a highly inflectional language script like Bangla (a major indian language). This is the first report of its kind. Using two separate lexicons ...
详细信息
This paper deals with an OCR error detection and correction technique for a highly inflectional language script like Bangla (a major indian language). This is the first report of its kind. Using two separate lexicons of root words and suffixes, candidate root-suffix pairs of each input word are detected, their grammatical agreement are tested and the root/suffix part in which the error has occurred is noted. The correction is made on the corresponding error part of the input string by a fast dictionary access technique. To do so some alternative strings are generated for an erroneous word. Among the alternative strings, those satisfying grammatical agreement in root-suffix and also having smallest Levenstein-Damerau distance are finally chosen as the correct ones. The system has an accuracy of 75.61%.
Postal automation is a topic of research over the last few years. There are many works towards the postal automation in USA, UK, Japan and Australia, but for indian postal automation there is no significant work. This...
详细信息
Postal automation is a topic of research over the last few years. There are many works towards the postal automation in USA, UK, Japan and Australia, but for indian postal automation there is no significant work. This paper deals with word-wise handwritten script identification for indian postal automation. In the proposed scheme at first document skew is detected and corrected. Non-text parts are then segmented from the document using run length smoothing algorithm (RLSA). Next, using a piece-wise projection method the destination address block (DAB) is at first segmented into lines and then links into words. Using water reservoir concept we compute the busy-zone of the word. Finally, using matra/Shirorekha, water reservoir concept based feature, etc. a tree classifier is generated for word-wise Bangla/Devnagari and English scripts identification.
The paper deals with an optical character recognition system for printed Oriya, a popular indian script. The development of OCR for this script is difficult because a large number of characters have to be recognized. ...
详细信息
ISBN:
(纸本)0769512631
The paper deals with an optical character recognition system for printed Oriya, a popular indian script. The development of OCR for this script is difficult because a large number of characters have to be recognized. In the proposed system, the digitized document image is first passed through preprocessing modules like skew correction, line segmentation, zone detection, word and character segmentation, etc. These modules have been developed by combining some conventional techniques with some newly proposed ones. Next, individual characters are recognized using a combination of stroke and run-number based features, along with features obtained from the concept of a water reservoir. The feature detection methods are simple and robust. A prototype of the system has been tested on a variety of printed Oriya material, and currently achieves 96.3% character level accuracy on average.
暂无评论