Content-Based Image Retrieval Process for Speech Annotated Digital Images
Objective
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.
Abstract
In this work, a new retrieval system for digital images has been presented which is based on speech to text conversion and customized bag-of-features workflow. Growing number of customers with huge of digital images in their computers, retrieving of images has become vital trouble in management of virtual photographs. Here, we will discuss about the Content Based Image Retrieval (CBIR) which is implemented in two phases.
One is conversion of speech to text
using third party cloud component called pocket sphinx, which is implemented on
Python. Second phase is the retrieval of images using customized
bag-of-features, which is implemented on Matlab. Our work will gives best
results when compared to existing methods.
Keywords:
Image
Retrieval, Content Based Image Retrieval (CBIR), Speech to text conversion,
Bag-of-features.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2018a or above and Python 3.6 or 3.7
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
- Introduction to Matlab
- What is EISPACK & LINPACK
- How to start with MATLAB
- About Matlab language
- Matlab coding skills
- About tools & libraries
- Application Program Interface in Matlab
- About Matlab desktop
- How to use Matlab editor to create M-Files
- Features of Matlab
- Basics on Matlab
- What is an Image/pixel?
- About image formats
- Introduction to Image Processing
- How digital image is formed
- Importing the image via image acquisition tools
- Analyzing and manipulation of image.
- Phases of image processing:
- Acquisition
- Image enhancement
- Image restoration
- Color image processing
- Image compression
- Morphological processing
- Segmentation etc.,
- How to retrieve the system using AI
- How to extend our work to another real time applications
- Introduction to Python
- How to start with Python
- About Python language
- Python coding skills
- About tools & libraries
- Application Program Interface in Python
- Package Installing in Python
- Importing Packages in Python
- About Python IDLE
- How to use Matlab editor to create PY Files
- Features of Python
- Basics on Python
- How to extend our work to another real time applications
- Project
development Skills:
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginary skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
Related Projects
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects, are not associated or affiliated with IEEE, in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, and not projects of or by IEEE.
