Sign Language Detection Using matlab

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Description

ABSTRACT:

HRI represents a challenge to involve humans and robots interact. The problem is robot does not understand the human?? language directly and HRI requires media for communication that can be both understood by a robot and easily done by a human, especially to help deaf people, patients, and old people, therefore gesture recognition as communication media is needed to give order to Robot. Machine learning is a part of Artificial Intelligence (AI) which discusses the development of a system that depends on information or data This paper discusses hand gesture recognition as an input command for Bioloid Premium Robot using two methods, Fuzzy C Means clustering and Support Vector Machine (SVM) with directed acyclic graph (DAG) decision K-Means clustering or Lloyd’s algorithm proposed the way to clustering some data which applying Euclidean idea of the distance between all data elements.


EXISTING SYSTEM

  • Thresholding method
  • Does K mean clustering
  • Manual analysis – is time-consuming, inaccurate, and requires an intensively trained person to avoid diagnostic errors.

Drawback

  • Difficulties are there to find the optimal gradient
  • Poor Edge detection.
  • Manual segmentation

PROPOSED SYSTEM

  • k-means clustering
  • convolutional neural network

Advantage:

1)Apriori specification of the number of clusters.
2)With a lower value of? ? we get a better result but at the expense of? more number of iterations.
3) Euclidean distance measures can unequally weight underlying factors.?

4) Output is obtained in form of both text and speech.


Block diagram

 

SIGN LANGUAGE DETECTION USING MATLAB
SIGN LANGUAGE DETECTION USING MATLAB

 


PREPROCESSING

Digital Image Processing. Digital image processing deals with? the manipulation of digital images through a digital computer. It is a subfield of signals and systems but focuses particularly on images. DIP focuses on developing a computer system that is able to perform?processing?on an? image. The input of that system is a digital?image?and the system process that?image?using an efficient algorithm

?It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing.

  1. Importing the image via image acquisition tools;
  2. Analyzing and manipulating the image;
  3. Output in which result can be altered image

Image Pre-processing is a common name for operations with images at the lowest level of abstraction. Its input and output are intensity images.? The aim of?pre-processing?is an improvement of the? image? or data that suppresses unwanted distortions or enhances some image? features important for further processing.


CONCLUSION

In this paper, we have designed a prototype model for dumb people. The important key factor of this project is to facilitate these people from these risk factors and to make them more confident to manage their sites by themselves.

And we can communicate with the blind by using artificial intelligence techniques.

The project will be beneficial to both dumb and as well as normal people in this electronic world. We are trying to make this project more and more convenient to mute people.

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