Content based Image Retrieval process for speech annotated digital images









Abstract

In this paper, a new indexing and retrieval system for digital pictures has been presented with speech notes based on syllable-converted picture-like samples. The growth in reputation of digital camera spots in the direction of growing number of customers with huge album of digital images in their computers which includes gloss and retrieval, has become known as vital trouble in management of virtual photographs. Usually, customers must type such advanced content manually and repetitively to comment on their snap shots. Multidimensional scaling is used to identify n-best users to deal with recognition errors and is converted into an image-like sample. Though the availability of an integrated microphone in maximum virtual cameras, consumer can now articulate about their pictures onto the spot and records these observations into machine readable documents. Recently in automatic voice recognition technology, speech gloss and retrieval gives an option and predictable strategy for existing photograph ordering, recovery methods and supplanting the repetitive work of manual writing. In speech annotation and retrieval, a hybrid mechanism is utilized to assimilate picture-like styles, syllables, words and characters.


Modules


Algorithms


Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL