Edit distance for a run-length-encoded string and an uncompressed string☆
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Cited by (18)
Binary image encryption in a joint transform correlator scheme by aid of run-length encoding and QR code
2018, Optics and Laser TechnologyCitation Excerpt :Meanwhile, the scrambling appends an additional security level on the cryptosystem. Run-length encoding (RLE) is known as an important coding approach achieving lossless data compression [28]. In RLE, a string will be divided into several runs, and each run consists of identical letters.
Efficient merged longest common subsequence algorithms for similar sequences
2018, Theoretical Computer ScienceCitation Excerpt :It is essential in many applications to measure the similarity of two sequences, such as computational biology, pattern matching, plagiarism detection, voice recognition, and so on. The most well-known methods for measuring the sequence similarity in computer science are the algorithms for the longest common subsequence (LCS) problem [1–4,6,7,12,19,32–35] and the edit distance problem [22–25,28]. There are some applications for the MLCS and BMLCS problems.
Hardness of comparing two run-length encoded strings
2010, Journal of ComplexityCitation Excerpt :Since then this has been an active research field, and several papers have delved into compressed pattern matching problems under various compression schemes (e.g., rle compression, LZ-family compression, or straight-line programs). For the rle scheme, some papers took one step further by considering problems of comparing two rle strings using different cost functions, such as the LCS metric [5,17,19], the Levenshtein distance [16,18], and arbitrary alignment scores [10,14]. In this paper, we investigate the hardness of comparing (or approximately matching) two strings both compressed into the rle format.
A fast and simple algorithm for computing the longest common subsequence of run-length encoded strings
2008, Information Processing LettersApproximating Dynamic Time Warping Distance between Run-Length Encoded Strings
2022, Leibniz International Proceedings in Informatics, LIPIcs
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This work was supported in part by the National Science Council of the Republic of China under Contract NSC 95-2221-E260-025.