Shridhar M. and Badreldin A., "Recognition of Isolated and Simply Connected Handwritten Numerals," Pattern Recognition, Vol.19, pp.1-12, 1986.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....The challenge of a segmentation technique lies in the decision of the best cut path to localize an entity to be recognized as a correct isolated character by the recognition system. The literature usually shows three different strategies to perform the segmentation : Segmentation Recognition [12] [16] Segmentation based Recognition [5] 11] and Segmentation Free systems [14] 15] In the first approach, the segmentation provides a single sequence hypotheses where each sub sequence should contain an isolated character, which is submitted to the recognizer. This technique shows rapidly ....

....our conclusions and our future works. 2 Generation of the Segmentation Features Depending on the context, a lot of features are available to find plausible segmentation points in a character image. Certainly some of the most used in the literature are the contour and profile features [7] 3] [12]. Indeed, these features are easy to be provided and they usually express directional variability of the character strokes and then possible cuts. However, they are not even fully informative to localize any kind of connection between characters, mostly when the handwriting is strongly skewed or ....

M.Shridhar and A.Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1--12, 1986.

....courtesy amount recognition belong to the class of digit recognition techniques although in many cases these amounts include also some non digit symbols such as commas, periods, strokes, currency names, etc. Strategies for digit string recognition can be divided into segmentation then recognition [30] and segmentation based recognition [26] In the rst approach, the segmentation module provides a single sequence hypothesis where each sub sequence should contain an isolated character, which is submitted to the recognizer. This technique shows its limits rapidly when the correct segmentation ....

M. Shridhar and A. Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):112, 1986.

....The challenge of a segmentation technique lies in the decision of the best cut path to localize an entity to be recognized as a correct isolated character by the recognition system. The literature usually shows three different strategies to perform the segmentation : SegmentationRecognition [6] Segmentation based Recognition [3] 5] and Segmentation Free systems [8] In the first approach, the segmentation module provides a single sequence hypotheses where each sub sequence should contain an isolated character, which is submitted to the recognizer. This technique shows rapidly its ....

....with binary images with a 300 dpi resolution. 2 Generation of the Segmentation Features Depending on the context, a lot of features are available to find plausible segmentation points in a character image. Certainly some of the most used in the literature are the contour and profile features [2] [6]. Indeed, these features are easy to be provided and they usually express directional variability of the character strokes and then possible cuts. However, they are not even fully informative to localize any kind of connection between characters, mostly when the handwriting is strongly skewed or ....

M.Shridhar and A.Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1--12, 1986.

....in tax and census forms. Such applications have been motivated by the availability of relatively inexpensive CPU power, and the possibility to reduce considerably the manual effort involved in these tasks. Strategies for numeral string recognition can be divided into segmentation then recognition [17] and segmentation based recognition [15] In the first approach, the segmentation module provides a single sequence hypothesis where each sub sequence should contain an isolated character, which is submitted to the recognizer. This technique shows its limits rapidly when the correct segmentation ....

M.Shridhar and A.Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1--12, 1986.

....and Suen [6] uses local features. They extract local geometric primitives consisting of line segments and convex polygons and use these as input to a structural classifier. Others extract topological features which depend on the global properties of the data. For example, Shridhar and Badreldin [7] use features derived from the character profiles in the image. They then feed these features into a tree classifier. More recently there have been a number [8] 9] 10] of successful attempts to automatically learn appropriate local features using feedforward neural networks. Some researchers ....

M. Shridhar and A. Badreldin, "Recognition of isolated and simply connected handwritten numerals", Pattern Recognition, vol. 19, no. 1, pp. 1--12, 1986.

....The challenge of a segmentation technique lies in the decision of the best cut path to localize an entity to be recognized as a correct isolated character by the recognition system. The literature usually shows three different strategies to perform the segmentation : Segmentation Recognition [12] [16] Segmentation basedRecognition [5] 11] and Segmentation Free systems [14] 15] In the first approach, the segmentation provides a single sequence hypotheses where each sub sequence should contain an isolated character, which is submitted to the recognizer. This technique shows rapidly its ....

....our conclusions and our future works. 2 Generation of the Segmentation Features Depending on the context, a lot of features are available to find plausible segmentation points in a character image. Certainly some of the most used in the literature are the contour and profile features [7] 3] [12]. Indeed, these features are easy to be provided and they usually express directional variability of the character strokes and then possible cuts. However, they are not even fully informative to localize any kind of connection between characters, mostly when the handwriting is strongly skewed or ....

M.Shridhar and A.Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1--12, 1986.

....pairs are actually overlapping. 5 Curved Pre Stroke Cuts To allow touching and kerned characters to be separated more cleanly, we allow the cuts to be curved. In fact, the idea of using curved lines for separating handwritten characters is not new (see, for example, the hit and deflect strategy [15, 16]) However, the approach taken in this paper is different both in how the location and the shape of cuts are identified. The basic idea is to use a dynamic programming algorithm to find a globally optimal set (according to a certain evaluation function to be specified below) of cuts through the ....

....component. If we considered the set of cuts passing through, say, each point (x, 0) difficult to segment regions of a connected component would simply be avoided by cuts; the cuts would navigate around such regions. This is a crucial difference to methods like the hit and deflect approach [15, 16]. An application of this method is shown in Figure 4. Curved black lines running through the string (FLIGHT ENGINEER) are cuts found by the method. The graph at the bottom shows the value of the cost function at each x coordinate and the location of local minima. Figure 6. The final set of ....

M. Shridhar and A. Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1--12, 1986.

....is this method which has been attempted here. After rudimentary character segmentation as described above, each character segment or zone has a center of gravity calculated and assigned. The baseline is defined as the best fitting straight line passing through the minima of the letter bodies (Shridhar and Baldredini, 1986, pp 8) and that is what this algorithm attempts. The aforementioned paper discussed a more elaborate approach which further subdivides the characters into 8 zones and averages the zones centers of gravity as well. This method, however, is too extravagant for our rudimentary needs, which are ....

.... for the stated purpose of determining ascenders and descenders, there is not much more that could be done to this algorithm in the future, although the area of normalization using zones as mentioned in Guerfali and Plamondon Practical Project Report December 15, 1993 22 (1993) as well as Shridhar and Baldredini (1986, pp. 4 7) are quite interesting, and would make an interesting term project on their own. A further aim of detecting a baseline was to make some rudimentary attempts at baseline correction using the aforementioned zones . This was not feasible, given the time constraints, but the code is ready ....

SHRIDHAR, M., BALDREDINI, A. (1986) "Recognition of Isolated and Simply Connected Handwritten Numerals", Pattern Recognition, Vol. 19, No. 1 pp. 1-12.

....and Suen [5] uses local features. They extract local geometric primitives consisting of line segments and convex polygons and use these as input to a structural classifier. Others extract topological features which depend on the global properties of the data. For example, Shridhar and Badreldin [6] use features derived from the character profiles in the image. They then feed these features into a tree classifier. More recently there have been a number [7] 8] 9] of successful attempts to automatically learn appropriate local features using feed forward neural networks. Some researchers ....

M. Shridhar and A. Badreldin, "Recognition of isolated and simply connected handwritten numerals", Pattern Recognition, vol. 19, no. 1, pp. 1--12, 1986.

....2. Off line: The off line method does not use a stylus and tablet. Instead, characters written on a paper are captured via a scanner or camera and then stored in a digitized form (that is, in binary or gray scale) Although, the on line method provides more information than the off line method [72, 75, 74], its use of a special writing tablet to collect information causes serious constraints on its application. This thesis concentrates on handwriting recognition problem for off line environment. Recognition of totally unconstrained handwritten numerals with high and reliable recognition rates has ....

M. Shridhar and A. Badreldin. Recognition of isolated and simply connected handwritten numerals. In Pattern Recognition, volume 19, no. 1, pages 1--12, 1986.

....This approach allows for the visualization and understanding of finest granularity of data written or printed on documents such as bank cheques. 7.11. Other Segmentation Techniques Document Analysis and Recognition by Computers 29 Segmentation techniques can be roughly categorized as [3, 84, 2, 68, 12, 25, 53]: ffl projection based, ffl pitch based, ffl recognition based, ffl region based. The first two techniques are suitable for typewritten texts where characters are equally spaced and there is a significant gap between adjacent characters. In the recognition based methods, segmentation is ....

....the input image components as well as how these components are related in order to detect suitable regions for segmentation. Also, segmentation techniques can be categorized as the following types by the sorts of pixels to be worked on: ffl Methods working on foreground pixels (black pixels) [3, 84, 68, 12, 25, 53], ffl Methods working on background pixels (white pixels) 14] 8. Conclusions Every day, millions of documents including technical reports, government files, newspapers, books, magazines, letters, bank cheques, etc. have to be processed. A great deal of time, effort and money will be saved if ....

M. Shridhar and A. Badreldin. "Recognition of isolated and simply connected handwritten numerals," Pattern Recognition, Vol. 19, No. 1, pp. 1-12, 1986.

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Shridhar M. and Badreldin A., "Recognition of Isolated and Simply Connected Handwritten Numerals," Pattern Recognition, Vol.19, pp.1-12, 1986.

No context found.

Shridhar M. and Badreldin A., "Recognition of Isolated and Simply Connected Handwritten Numerals," Pattern Recognition, Vol.19, pp.1-12, 1986.

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M. Shridhar and A. Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):112, 1986.

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M. Shridhar and A. Badreldin, "Recognition of Isolated and Simply Connected Handwritten Numerals," Pattern Recognition, vol. 19, no. 1, pp. 1-12, 1986.

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M. Shridhar and A. Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):112, 1986.

No context found.

M. Shridhar and A. Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):112, 1986.

No context found.

M.Shridhar and A.Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1-12, 1986.

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M. Shridhar and A. Badreldin, Recognition of isolated and simply connected handwritten numerals, Pattern Recognition,vol.19, no.1, 1#12 #1986#

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M.Shridhar and A.Badreldin. Recognition of isolated and simply connected handwritten numerals. Pattern Recognition, 19(1):1-12, 1986.

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M. Shridhar and A. Badreldin, Recognition of isolated and simply connected handwritten numerals, Pattern Recognition, vol.19, no.1, 1--12 (1986)

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