AU2021101278A4 - System and Method for Automatic Language Detection for Handwritten Text - Google Patents

Abstract

System and Method for Automatic Language Detection for Handwritten Text In the view of transformations of technology and embedded with smart system has been taken more attention since 1990s. Automatic language detection (ALD) for handwritten text are perform by novel method and system device. Indeed, ALD system is deploy prior to sending specific descriptions of the handwritten texts to recognition section. However, multi-input could be considered for this interface, which is associated with coordinates of the inputs entity and time period recorded for inputs. Meanwhile also need to focus on groups of text (handwritten) inputs and transform in terms of word based on the coordinates and time span. Hereafter it will be form of writing strokes for regularising process and individual words will be process for generate language vectors. Moreover, the language vectors will be recognised the probabilities of language of the handwritten texts through recurrent neural network (RRN). In addition, based on language probabilities output, the handwritten inputs are transfer to a specific language recognition system for determined the language thereof before to translation.

Description

TITLE OF THE INVENTION

System and Method for Automatic Language Detection for Handwritten Text

FIELD OF THE INVENTION

This invention relates to a system and method of Automatic language detection (ALD) for handwritten text are perform by novel device.

BACKGOUND OF THE INVENTION

Automatic handwritten recognition systems permit to user about inputs the handwritten text for transformed into the word form. In current inventions allow to user to input handwritten text and also need to download the language packs for better performed the transformation functions. It has been obserded that online system having the translations system, which is provide strokes of handwritten text into available language (in database). However, for calibrating point of view the confidence scores from each corresponding to meaningful picked the correct results is complex and difficult. And such approach does not work in large scale with good accuracy. Moreover, the language recognizers produce result and sufficient suggestions in several language inputs.

AU 2015318386 B2: Hu, Yulong; Zhang, Yintian; Zhu, Bo;Wei, Si; Hu, Guoping; Hu, Yu; Liu, Qingfeng: An intelligent scoring method and system for a text objective question, the method comprising: acquiring an answer image of a text objective question (101); segmenting the answer image to obtain one or more segmentation results of an answer string to be identified (102); determining whether any of the segmentation results has the same number of characters as the standard answer (103); if no, the answer is determined to be wrong (106); otherwise, calculating identification confidence of the segmentation result having the same number of words as the standard answer, and/or calculating the identification confidence of respective characters in the segmentation result having the same number of words as the standard answer (104); determining whether the answer is correct according to the calculated identification confidence (105). The method can automatically score text objective questions, thus reducing consumption of human resource, and improving scoring efficiency and accuracy.

US 8,014,603 B2: Jose A. Rodriguez Serrano, Florent C. Perronnin; method of characterizing a word image includes traversing the word image stepwise with a window to provide a plurality of window images. For each of the plurality of window images, the method includes splitting the window image to provide a plurality of cells. A feature, such as a gradient direction histogram, is extracted from each of the plurality of cells. The word image can then be characterized based on the features extracted from the plurality of window images.

US 10, 185, 882 B2: Yousef S. I. Elarian; Systems and associated methodology are presented for Ara bic handwriting synthesis including accessing character shape images of an alphabet, determining a connection point location between two or more character shapes based on a calculated right edge position and a calculated left edge position of the character shape images extracting character features that describe language attributes and width attributes of characters of the character shape images , the language attributes including character Kashida attributes, and generating images of cursive text based on the character Kashida attribues and the width attribues.

US 10,643,067 B2: Romain Bednarowicz; Robin M6Linand; Claire Sidoli; Fabien Ric; Khaoula Elagouni; David Hebert; Fabio Valente; Gregory Cousin; Ma1 Nagot; Cyril Cerovic; Anne Bonnaud; A system, method and computer program product for hand drawing diagrams including text and non - text elements on a computing device are provided. The computing device has a processor and a non - transitory computer readable medium for detecting and recognizing hand - drawing diagram element input under control of the processor. Display of input diagram elements in interactive digital ink is performed on a display device associated with the computing device. One or more of the diagram elements are associated with one or more other of the diagram elements in accordance with a class and type of each diagram element. The diagram elements are re - displayed based on one or more interactions with the digital ink received and in accordance with the one or more associations.

US 2018 / 0137350 Al: Felipe Petroski SUCH; Raymond PTUCHA; Frank BROCKLER; Paul HUTKOWSKI; Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined thresh old. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.

US 8,077,973 B2: Jianxiong Dong; A method of recognizing a handwritten word of cursive Script includes providing a template of previously classified words, and optically reading a handwritten word so as to form an image representation thereof comprising a bit map of pixels. The external pixel contour of the bit map is extracted and the Vertical peak and minima pixel extrema on upper and lower Zones respectively of this external contour are detected. Feature vectors of the vertical peak and minima pixel extrema are determined and compared to the template so as to generate a match between the handwritten word and a previously classified word. A method for classifying an image representation of a handwritten word of cursive script is also provided. Also provided is an apparatus for recognizing a handwritten word of cursive Script.

US 10 , 156 , 982 B1: Sabri A . Mahmoud; Baligh M . Al -Helali; A character recognition device includes circuitry that is configured to remove duplicate successive points of a plurality of points in a handwritten stroke to form an enhanced handwritten stroke; space the plurality of points a uniform distance apart; detect primary strokes and secondary strokes of the enhanced handwritten stroke; merge the primary strokes; generate a primary merged stroke; extract raw point - based features from local features of the primary merged stroke; extract statistical features from computed statistics associated with the raw point - based features to form primary merged stroke features ; train and classify data from the primary merged stroke features and secondary stroke features to form stroke models; determine a plurality of primary merged stroke model candidates from the stroke models; compute a likelihood value for a combined set of primary stroke candidates and a set of secondary stroke candidates; and determine the handwritten stroke from the computing.

SUMMARY OF INVENTION:

Handwritten text systems are generally used for various applications and now-a-days this technology is booming. Prior to implementation of this technology, which was dependent on writing texts with our own hands and languages. However, it is difficult to store in huge quantity, access physical data and process the efficient manner, due to manual management. Since for long time it has been encountered a severe loss of data because of the traditional method of storing data. In current scenario various technological tools are introduced based on handwritten texts, and because of these tools now it is easier to store a huge data inn single click. The implementation of handwritten text recognition device is a real-world idea for easy storing of precious data. Moreover, the invention reveals and make a model for recognitions of handwritten texts, which will be help to recognized of multiples handwritten text (available in database system i.e., language packages). Fig. 1, shows the functional activity of current invention, and this function is used for translating the handwritten texts to word form text.

The scope of present invention is not only limited to disclosed embodiments but also includes combinations of the disclosed embodiments, as well as modifications to the disclosed embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS:

[0003] Fig. 1: Schematics block-diagram of current developments. It is comprising with four embedded system like (1) Image's acquisition system, (2) Digitization rendering, (3) Pre processing of inputs (handwritten text), (4) Feature analysis. This system will be help for performing the translation of handwritten text as per database input or may depends on language packages.

DETAILED DESCRIPTION OF THE INVENTION:

In the current inventions are primarily reliant on the ensuing measuring aspect: (a) Recognition approaches are profoundly exertion on the nature of the data (style of handwritten text) to be recognized. (b) As the letters in the word are generally linked together, critically written and may even be missing.

The disclosed embodiments provide of ALD which will be performed before sending representations of the handwritten text to a language recognition tool to scale back performance penalties for text translations. That is by determining a selected language recognition tool to be utilized before text translation rather than translating text across multiple engines for every translation, resource utilization is greatly reduced. Accordingly, techniques are provided herein for efficient performance of ALD for handwritten text and its translation that permits implementations to be utilized on people and authority devices. Performing the described ALD is not source concentrated, unlike earlier explanations, through the pre-determination of languages for handwritten text, and thus does not needed a source heavy server to performing. It is contemplated herein that any sorts of languages could also be determined from handwritten text in accordance with the disclosed embodiments.

In an embodiment, a language determination is formed, word by word, before selecting a language recognition tool and attempting translations of handwritten text. That is, a soft decision is formed, based a minimum of on the handwritten text inputs, such one or specific language recognition tool could also be run to acknowledge the inputs. Groups of strokes could also be determined as words based a minimum of on coordinates of the strokes with reference to the input interface and every other, and therefore the time at which the strokes are made with reference to one another.

10007] The inputs, as words, could also be provided to a language generic tool to detect indicia of the language for the handwritten text inputs before they are sent to a selected language recognizer. The generic tool may include several components such as but not limited to an RNN. The RNN takes featured inputs and generates output vectors. The output vectors of the RNN are provided to the soft decision tool to get language probabilities for the handwritten text.

Afterward, a selected language recognition tool could also be identified and select. The handwritten text inputs could also be provided to the identified specific language recognition tool for a final determination of the language, allowing the handwritten text inputs to be translated by one translation tool. As words are translated, it will be provided on a demonstration device for observing and choice by a user.

EDITORIAL NOTE 2021101278

There is 1 page of claims only.

Claims (4)

Claims:

1. A technique of portraying of handwritten text and capturing the text image comprising with handwritten text to translating to word form;

2. The method of claim 1, further comprising: for each window image, determining a features vector based on the extracted features of each of the handwritten text;

3. The method of claim 2, wherein the computation of the features vector comprises concatenating the extracted features of handwritten text;

4. The method of claim 1, A complete processing system which executes about instructions stored in tool for performing the method of claim 1.

Fig. 1: Schematics block-diagram of current inventions.