IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

Missing Child Identification System using HOG and KNN Machine Learning Classifier

Main Article Content

Dr. Prabagar S , M Shahid Afrid , P Taraka Sai Tarun ,B Praneeth Kumar Reddy ,M Govardhan Reddy

Abstract

In India, a countless number of children are reported missing every year. Among the missing child cases, a large percentage of children remain untraced. This paper presents a novel use of deep learning methodology for identifying the reported missing child from the photos of a multitude of children available, with the help of face recognition. The public can upload photographs of a suspicious child into a common portal with landmarks and remarks. The photo will be automatically compared with the registered photos of the missing child from the repository. Classification of the input child image is performed and the photo with the best match will be selected from the database of missing children. For this, the machine learning model is trained to correctly identify the missing child from the missing child image database provided, using the facial image uploaded by the public. In this system, for face detection, we are using a HOG (Histogram of oriented Gradient) based face detector which gives more accurate results rather than other methodologies like Haar Cascade and CNN.

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