Script separation in machine printed bilingual (Devnagari and Gurumukhi) documents using morphological approach

We have developed a method that makes it easier for language beginners to look up Japanese kanji characters. Instead of using the arbitrary conventions of kanjis, this method is based on three simple prototypes: horizontal, vertical, and other strokes. For example, the code for the kanji \(\boxplus\) (ta, meaning rice field) is ‘3-3-0’, indicating the kanji consists of three horizontal strokes and three vertical strokes. Such codes allow a beginner to look up kanjis even with no knowledge of the ideographic conventions used by native speakers. To make the search easier, a complex kanji can be looked up via the components making up the kanji. We conducted a user evaluation of this system and found that non-native speakers could look up kanjis more quickly and reliably, and with fewer failures, with our system than with conventional methods.

In this paper, we propose a new approach for off-line intelligent word recognition. Firstly, we segment a word into its single characters. Then, we tag every pixel of a character as vertical or horizontal and group them into vertical and horizontal strokes. We propose as main features the locations of the joints between a vertical stroke and each of their adjacent horizontal ones. These features can easily be obtained by dynamic zoning. After that, a Deterministic Finite Automaton (DFA) along with a regular grammar, let us generate a representative string of the above mentioned features. For the experiments we constructed sets of synthetic words from real characters written by two different authors to generate a knowledge base for each of the writers with the strings provided by the DFA. To achieve the recognition, we use an Inference Engine that matches representative strings of characters from unknown test words with those characters stored in the Knowledge Base. The experiments provide promising results.

A trial approach is presented for the realization of an optical character reader for printed Chinese characters (kanji). This approach is different from conventional ones as far as kanji features and recognition are concerned. Use is made of structural features based on only the horizontal and vertical strokes in a kanji, taking advantage of optical/digital hybrid processing. The recognition experimental results are promising: 99.6%, 0.3%, and 0.1% for the correct, rejected, and error rates, respectively.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

We developed a method to enter Hiragana (cursive in Japanese) characters and alphanumeric characters by thumb gestures for Japanese people. This method is optimized to be used while holding the left and right ends of a tablet PC with hands. Each gesture is designed by concatenating a few horizontal and/or vertical strokes, but path of the gesture remains inside the one-stroke square centering its starting position. A Hiragana character is input by selecting a row of the table of Japanese syllabary and then a column of the table. The alphabet characters are segmented into 6 groups in order of letters. Just like Hiragana, an alphabet character is entered by selecting a group and then selecting a member. However, in the alphanumeric mode, to reduce the cost of modifying the mistakenly selected group, an operation to move to the previous or next group have been added.

The recognition rate of OCR (optical character recognition) systems often decreases for degraded text images, such as stroke-connected, stroke-broken and noisy text images. In this paper a unified method for preprocessing binary text images based on mathematical morphology is presented. Simple but effective morphological filters are designed to process stroke-connected and stroke-broken images separately. A method to classify stroke-connected and stroke-broken text images based on the horizontal and vertical average stroke width is also presented. A morphological contour filter is used for removing noise. Experimental results show that the result of the preprocessing method are satisfactory.

Characterization of the fine motor problems in patients with cognitive dysfunction – A computerized handwriting analysis

On-line size control in handwriting demonstrates the continuous nature of motor programs

Total alloplastic temporomandibular joint (TMJ) replacement has become common. This in vitro study aimed to evaluate wear response of custom-fabricated electron beam melted titanium (EBM-Ti), zirconia, and acrylic TMJ parts when subjected to biomechanical simulation testing. Eighteen prosthetic TMJ parts (condyle, glenoid fossa) were custom-fabricated using computer aided design and manufacturing (CAD/CAM) techniques based on patient’s radiographic images. Biomechanical simulation testing of TMJ parts (in different combinations) were done in a modified chewing simulator (108,000 cycles, 1 Hz frequency, 45–60 N compression, strokes-downward 0.15–0.25 s/horizontal, 0.4–0.5 s/upward, 0.25–0.45 s/displacement, 1.5–2.0 mm). Qualitative analysis using scanning electron microscopy revealed wear facets on leading edges of vertical and horizontal simulation strokes. Measurement of pre-test and post-test weights of TMJ parts revealed non-significant reduction in weights due to wear. EBM-Ti and acrylic TMJ glenoid fossae articulating against zirconia condyles during simulation testing had significantly higher wear, evidenced by greater mean reduction in weights. Based on results of this preliminary study, custom-fabricated alloplastic prosthetic TMJ are a viable alternative to stock alloplastic joints. While EBM-Ti and acrylic are suitable biomaterials for custom-fabrication, use of zirconia results in greater wear and requires further studies to optimize their role in customized alloplastic TMJ.

Analysis of phasic and tonic electromyographic signal characteristics: Electromyographic synthesis and comparison of novel morphological and linear-envelope approaches

In order to cope with the ambiguity of spatial relative position concepts, we propose a new definition of the relative position between two objects in a fuzzy set framework. This definition is based on a morphological and fuzzy pattern-matching approach, and consists of comparing an object to a fuzzy landscape representing the degree of satisfaction of a directional relationship to a reference object. It has good formal properties, it is flexible, it fits the intuition, and it can be used for structural pattern recognition under imprecision. Moreover, it also applies in 3D and for fuzzy objects issued from images.

Segmentation is one of the important steps of character recognition system. It is an important step because inaccurate segmentation of characters will cause errors in the recognition stage. In optical character Recognition (OCR) system the presence of touching characters and broken characters decreases the accuracy rate of character recognition. Touching of half character or full character with other full character makes the character segmentation very challenging or difficult task. Segmentation of the broken character is quite difficult because vertical profile projection technique assumes the broken parts of the characters as individual characters. In this paper, we have proposed the method of segmentation for touching and broken characters of handwritten Punjabi text that is the Gurumukhi script. The main purpose of this paper is to provide the new segmentation technique based on neighboring pixels for broken characters and increase the accuracy for touching characters.

This work proposes a new stroke based methodology for handwritten character recognition. After the pre-processing, several steps are involved to achieve the recognition. First, the character is segmented into its strokes. Then, we determine the maximum length of the longest horizontal segment that can be inscribed on a stroke. We also compute that for the vertical direction. So we decide whether the stroke must be tagged as horizontal or vertical. After that, we represent by a string the vertical stroke position and its relational-ship with its adjacent horizontal strokes. In that string, each vertical stroke is represented by a character followed by a set of numbers which means where the adjacent horizontal strokes join the vertical one. A formal language grammar has been set and a knowledge base developed with known characters written by a single writer. Finally, an inference engine allow us to recognize unknown characters written by that single user. This algorithm has been tested on different writers and provides a hit rate of 87,13%.

During the first and second centuries A. D., Roman cursive developed a system of ligatures between letters that was to remain virtually unchallenged until a new cursive structure came about in the twelfth and thirteenth centuries. This remarkably coherent system was based on top-down connections, in the form of angular joins between the last, horizontal stroke of one letter and the first, vertical and downward stroke of the next; but from the outset different combinations, although sporadic, even exceptional, are evidence that other solutions were technically possible, namely bottom-up connections, particularly between vertical strokes. Why, then, was a broad range of artifices developed to enable the use of top-down, angular connections even with letters whose «natural» forms were incompatible, instead of resorting more widely to upstrokes? Mainly because this type of ligature was quite similar to the manner in which scribes tended to arrange the strokes constituting letters; the ligatures were consistent with a certain organisation of handwriting, which they in turn conditioned. This is all the more apparent in the fourth century when the structure of cursive letter forms and ligatures both developed in the same direction: although bottom-up connections remained relatively scarce and specific to certain variant letter forms (quite different in nature from medieval cursive ligatures), they henceforth became part of the system.

A new type of nonlinear image processor based on morphological processing is demonstrated. Morphological image processing is based on the successive binary convolution of an image with a selectable convolution kernel. Its field of application includes numerical optical computing and binary image processing. Simple serial commands from a small electronic computer control the selection of the convolution kernels for a given iteration and consequently the parallel processing of very large optical data planes. 1.

A lot of literature is available on the recognition of handwriting on scripts other than Indians, but the number of articles related to Indian scripts recognition such as Gurumukhi are much less. Gurumukhi is a religion-specific language that ranks 14th frequently spoken language in all languages of the world. In Gurumukhi script, some characters are alike to each other which makes recognition task very difficult. Therefore this article presents a novel approach for Gurumukhi character. This article lays emphasis on convolutional neural networks (CNN), which intend to obtain the features of given data samples and then its mapping is being performed to the right observation. In this approach, a dataset has been prepared for 10 Gurumukhi characters. The proposed methodology obtains a recognition accuracy of 99.34% on Gurumukhi characters images without making use of any post-processing method.