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Readiris™ 14 is a powerful OCR software designed to convert all your paper documents ...​ ... Image to OCR Converter is a text recognition software that can read text from bmp, pdf, tif, jpg, gif, png and all major image formats.​ ... VeryPDF Scan to Word OCR Converter can be used to convert ...

Figure 20.7 Raw skeleton resulting from a noisy input image. (a) 3D image of an artificial object with 20 % random noise; and (b) raw skeleton with spurious noise branches.

doOperation()

applyFormat()

4 3 3 3 4 4 4 2 2 5

Apply container, paragraph, and character formats to applicable elements in the selection Apply the appropriate kind of format to applicable elements in the selection



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of P is offset by 2 in Ps The element in position 1 of P is a 2 and the 2 4 4 appears in position 4 of Ps, so these have an offset of 3 Continuing in this manner, we see that the offsets, or differences, between the elements of P 4 and the corresponding elements of Ps are ( 2 , 3 , 1 , 4 , 1 ,3,O) As explained in Section 223, consecutive permutations from a rotor all share the same difference sequence The difference sequence for Ps and Ps: is different than between P and P5, so we can be sure that these three permutations were not 4 generated by consecutive shifts of a single rotor Now if we compute the difference sequence for permutations P and PCJ, 8 we see that it is the same as for P and Ps.





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applyContainerFormat(), applyParagraphFormat(), applyLeafFormat() applyLink(), applyTCY()

Figure 20.8 Skeleton after branch filtering. (a) Voxel representation of the filtered skeleton; and (b) point representation showing significant noise distortion.

Change selected text into a link element or TCY element, or back into a span Insert text or inline graphics at the active selection position Delete the selected text Delete the character or word neighboring the active selection position

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This is not coincidental In 4 fact, it is consistent with these two pairs being compositions of (non-rotor) permutations; see Problem 17 It was precisely this sort of observation that was the crucial breakthrough in the diagnosis of Purple Once we realize that the permutations in Table 26 are conipositions of permutations, we can solve for the individual permutations (or an equivalent set) as follows Most likely, P and Ps are consecutive fast permutations 4 with the same settings for the medium and slow permutations Suppose the L switch is the fast switch arid let LO be the fast permutation in P and L1 4 be the fast permutation in Ps Then RiMjLo(0) = RihfjL1(2),for some i and j , which implies that Lo(O) = L l ( 2 ) Continuing, we can determine the permutation L1 in terms of Lo Using the appropriate rows from Table 2.

insertText(), insertInlineGraphic() deleteText() deleteNextCharacter(), deletePreviousCharacter(), deleteNextWord(), deletePreviousWord() splitParagraph()

Split the paragraph at the active selection position, creating a new ParagraphElement Delete the selection, returning it as a TextScrap Insert the TextScrap, replacing the current selection Undo or redo the most recent operation Return whether you can perform an undo or redo Return the next undo or redo operation without removing it from the stack Return the next undo or redo operation as an IOperation, removing it from the stack but without performing it Adds an operation to the undo or redo stack

6, we can also determine L2 in terms of LOThen we are free to arbitrarily select Lo, thereby fixing L1 and L2 With the L permutations determined, we can similarly determine the A!! permutations Finally, when determining the R permutations, there will be no freedom to specify one of the permutations; see Problem 18 at the end of this chapter for more details on this particular example Is it feasible to obtain data analogous t o that in Table 26 for the Purple cipher If there happens to he a large number of messages in depth with known plaintext, then the encryption permutations are at least partially exposed by the various legs of depth, and the more legs of depth available, the more information there is on the underlying permut,ation at each position.

cutTextScrap()

distortions caused by image noise clearly visible in Figure 20.8(b) still need to be corrected. This problem is addressed in the next section.

pasteTextScrap() UndoManager undo(), redo()

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