An enhanced text detection technique for the visually impaired to read text

Joan, S. P. Faustina; Valli, S.

doi:10.1007/s10796-016-9699-x

Cited by 16 publications

(4 citation statements)

References 42 publications

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“…The article titled BAn Enhanced Text Detection Technique for the Visually Impaired to Read Text,^by Joan and Valli (2017) presents an enhanced text detection technique (ETDT) that aids the visually impaired to overcome their reading challenges. Their approach enhances the edge preserving maximally stable extremal regions (eMSER) algorithm using the pyramid histogram of oriented gradients (PHOG).…”

Section: In This Special Issuementioning

confidence: 99%

Guest Editorial: Computational Intelligence and Applications

et al. 2017

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Section: In This Special Issuementioning

confidence: 99%

Guest Editorial: Computational Intelligence and Applications

et al. 2017

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“…During shopping, PVI can then retrieve and use their lists. Several applications take an image from a printed text, a written list, or Braille and send it to an Optical Character Recognition (OCR) module, which analyses and converts it to text [49][50][51]. In some cases, the system sends the image to a character recognition API in cloud computing, which identifies the words and converts it to text [52].…”

Section: Shopping Preparationmentioning

confidence: 99%

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

2019

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People with visual impairment face various difficulties in their daily activities in comparison to people without visual impairment. Much research has been done to find smart solutions using mobile devices to help people with visual impairment perform tasks like shopping. One of the most challenging tasks for researchers is to create a solution that offers a good quality of life for people with visual impairment. It is also essential to develop solutions that encourage people with visual impairment to participate in social life. This study provides an overview of the various technologies that have been developed in recent years to assist people with visual impairment in shopping tasks. It gives an introduction to the latest direction in this area, which will help developers to incorporate such solutions into their research.

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“…Thus, the inability of reading a particular script might mislead the audience, who understand the corresponding language but are unable to recognize the title from the script. Moreover, for the visually impaired [9] or color-blind [10] persons, this application is a useful assisting system. That is, a script identification system can serve as a precursor, and help to decide the optical character recognition (OCR) [12] engine and recognize the title of the movie.…”

Section: Introductionmentioning

confidence: 99%

Movie Title Extraction and Script Separation Using Shallow Convolution Neural Network

et al. 2021

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Graphical texts in natural images play an important role in portraying information in multitudinous fields such as communication, education, and entertainment to name a few. Recognizing text in scene images is challenging due to the inherent complexity of the images. Text recognition in natural images involves script identification, which requires text localization. This is not trivial for natural scene images due to the presence of disparate foreground/background components. For scene images like movie posters, the challenge is more dominant. The challenges aggravate due to the presence of composite characteristics of posters like complex graphics background and the presence of different texts like a movie title, names of actors, producers, directors, and tagline. These texts have miscellaneous fonts, variations in colors, size, orientation, and textures. In this work, an M-EAST (modified EAST) model is proposed, which is based on the EAST (efficient and accurate scene text detector) model for text localization. A novel movie title extraction is thereafter used for separating the title from the extracted text pool. Finally, the title script was identified using a shallow convolutional neural network (SCNN)-based to ensure functionality in low-resource environments. Experiments were performed on a dataset of movieposter images of Tollywood, Bollywood, and Hollywood industries, and a highest accuracy of 99.82% was obtained. The system performed better than the reported techniques.

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An enhanced text detection technique for the visually impaired to read text

Cited by 16 publications

References 42 publications

Guest Editorial: Computational Intelligence and Applications

Guest Editorial: Computational Intelligence and Applications

Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

Movie Title Extraction and Script Separation Using Shallow Convolution Neural Network

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