01909nas a2200253   4500000000100000000000100001008004100002260001200043653002200055653001500077653002000092653002100112653001900133653002500152100002000177700002700197700001400224245011200238856008200350300001200432490000600444520119100450022001401641       2021                            d  c12/202110aMultilingual Text10aClustering10aComputer vision10aImage Processing10aMaxmin Cluster10aArbitrarily-Oriented1 aH.T. Basavaraju1 aV.N. Manjunath Aradhya1 aD.S. Guru00aNeighborhood Structure-Based Model for Multilingual Arbitrarily-Oriented Text Localization in Images/Videos  uhttps://www.ijimai.org/journal/sites/default/files/2021-11/ijimai7_2_12_0.pdf  a134-1400 v73 aThe text matter in an image or a video provides more important clue and semantic information of the particular event in the actual situation. Text localization task stands an interesting and challenging research-oriented process in the zone of image processing due to irregular alignments, brightness, degradation, and complexbackground. The multilingual textual information has different types of geometrical shapes and it makes further complex to locate the text information. In this work, an effective model is presented to locate the multilingual arbitrary oriented text. The proposed method developed a neighborhood structure model to locate the text region. Initially, the maxmin cluster is applied along with 3X3 sliding window to sharpen the text region. The neighborhood structure creates the boundary for every component using normal deviation calculated from the sharpened image. Finally, the double stroke structure model is employed to locate the accurate text region. The presented model is analyzed on five standard datasets such as NUS, arbitrarily oriented text, Hua's, MRRC and real-time video dataset with performance metrics such as recall, precision, and f-measure.  a1989-1660