000			03037nam a22003377a 4500
003			OSt
005			20240506045115.0
008			240504b ||||| |||| 00| 0 eng d
040			_bEnglish. _cCvSU-CCAT Campus Library. _erda.
050			_aUM QA 76.8 _bG86 2019
100			_aGumagay, Dharissa Lyn P., author. _911871
245			_aTextractor : a mobile application using digital image processing / _cDharissa Lyn P. Gumagay, Josephine S. Masamoc, and Ariel S. Acal.
260			_aRosario, Cavite : _bCavite State University-CCAT Campus, _c2019.
300			_axiii, 59 leaves : _billustrations ; _c28 cm
500			_aAn Undergraduate Thesis (BSCS) -- Cavite State University-CCAT Campus, 2019.
504			_aIncludes bibliographical references and appendices.
520			_aGUMAGAY, DHARISSA LYN P., MASAMOC, JOSEPHINE S., ACAL, ARIEL S. TexTractor: A Text Extractor Mobile Application Using Digital Image Processing. Cavite State University-CCAT, Rosario, Cavite. May 2019. Adviser: Prof. Christopher G. Estonilo. The study was conducted from August 2018 to April 2019 at the Department of Computer Studies of Cavite State University-CCAT. The general objective of the study was to extract the camera-captured printed characters into digital format using image processing. Specifically, the study aimed to 1) design and develop the mobile application using Phyton-Tesseract, which is capable of capturing the printed text using cellphone camera, separating the text from captured image aligned to it, editing and saving the text into pdf or text file format, and understand the saved text through text-to-speech of the cellphone; 2) evaluate the mobile application that comply with the ISO-IE 25010 software evaluation standards, and 3) prepare an implementation plan for the deployment of the mobile application in PlayStore and can be utilized by the users. The system analysis and design of TexTractor applied the rapid application development or RAD software development model which was composed of requirement analysis, user design (prototype, test, refine), construction, and cutover. The mobile application was evaluated by five (5) IT experts and (20) general end- user in the campus. It gained an average score of 4.50 and described as Very Satisfactory for the IT experts respondents. On the other hand, it gained a mean of 4.68 and described as Excellent for the end-users.
546			_aIn English text.
650			_aMobile applications. _911872
650			_aCharacter Recognition. _911873
650			_aPython (Computer Programming Language). _911874
650			_aScene text extraction. _911875
650			_aMobile phone camera. _911876
650			_aTranslation. _911877
700			_aMasamoc, Josephine S., author. _911878
700			_aAcal, Ariel S., author. _911879
700			_aEstonilo, Christopher G., adviser. _95822
700			_aNabablit, Karlo Jose E., technical critic. _99160
942			_2lcc _cT/M/D _hQA 76.8 G86 2019 _kUM
999			_c3252 _d3252