Design and implementation of a lip reading system in smart phone environment

During the recent years mobile phones' usage and their application in the everyday life has increased dramatically. Therefore the modern methods of security in mobile phone applications are highly regarded especially in mobile banking applications. In this paper, a novel security method is introduced in which a password is received using visual information processing from the user's lips. Phone Camera can provide the ability to track user's lip motion using lip reading algorithms to recognize the security words like passwords. Mobility in mobile phones has led to a change in ambient light. In this research, a method has been proposed to solve light change challenges in mobile phones. Finally an m-commerce android application is designed and implemented using this technique. The application recognizes passwords using automatic lip reading and checks whether the password is correct or not. If password is correct, the user can open his/her bank application. The reliability of this method is evaluated comparing with the traditional method of password protection in mobile phones.

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“…Another problem in mobile phones is people's mobility [17]. Mobility leads to environment, background and ambient light changing.…”

Section: Experiments Resultsmentioning

confidence: 99%

Mobile phone security using automatic lip reading

Lesani

Ghazvini

Dianat

2015

2015 9th International Conference on E-Commerce in Developing Countries: With Focus on E-Business (ECDC)

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“…Ma et al [3] developed a Bayesian model for lip-reading patterns under moderate noise exposure. Meanwhile, along with the development of communication tools, Kim et al [4] developed a method of lip-reading in a real time fashion for smart phones. Lip-reading method applied to several languages was developed by Saitoh et al [5], while Shin et al [6] developed this system for Korean language.…”

Section: Introductionmentioning

confidence: 99%

Lip Motion Pattern Recognition for Indonesian Syllable Pronunciation Utilizing Hidden Markov Model Method

2015

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A speech therapeutic tool has been developed to help Indonesian deaf kids learn how to pronounce words correctly. The applied technique utilized lip movement frames captured by a camera and inputted them in to a pattern recognition module which can differentiate between different vowel phonemes pronunciation in Indonesian language. In this paper, we used one dimensional Hidden Markov Model (HMM) method for pattern recognition module. The feature used for the training and test data were composed of six key-points of 20 sequential frames representing certain phonemes. Seventeen Indonesian phonemes were chosen from the words usually used by deaf kid special school teachers for speech therapy. The results showed that the recognition rates varied on different phonemes articulation, ie. 78% for bilabial/palatal phonemes and 63% for palatal only phonemes. The condition of the lips also had effect on the result, where female with red lips has 0.77 correlation coefficient, compare to 0.68 for pale lips and 0.38 for male with mustaches.

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Lip segmentation and tracking based on Chan-Vese model

Nasuha

Sardjono

Purnomo

2013

2013 International Conference on Information Technology and Electrical Engineering (ICITEE)

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Lip reading has wide spread application, e.g. audio-visual Automatic Speech Recognition (A V-ASR), silent speech interface and person identification. Lip segmentation is one of important step in lip reading, because it provides basic information to be processed in subsequent steps. Lip tracking is a process of locating lip to associate lip in consecutive video fr ames. Chan-Vese model is a region-based segmentation algorithm, which also can be used as tracking method. This algorithm can detect boundary of object which not defined by gradient, while classical active contour can't be applied. This method also can detect object by any initial curve in the image, not necessarily surround the obj ect. This paper investigates about lip segmentation and tracking based on Chan-Vese model, preceded by the color segmentation.

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Design and implementation of a lip reading system in smart phone environment

Cited by 6 publications

References 3 publications

Mobile phone security using automatic lip reading

Mobile phone security using automatic lip reading

Lip Motion Pattern Recognition for Indonesian Syllable Pronunciation Utilizing Hidden Markov Model Method

Lip segmentation and tracking based on Chan-Vese model

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