Periscope: A Content-based Image Retrieval Engine

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Periscope is a Content-Based Image Retrieval web application. The repository of the project can be found here: https://github.com/AndyFou/Periscope

Daten & Analysen

Periscope: A Content-Based Image
Retrieval Engine
By Antigoni M. Founta
Student ID: 647

Components
The essential components of the
project!
● Python
● PostgreSQL
● OpenCV
● Scikit-Image
● Python Libraries: ScıPy, NumPy
● Flask
● Bootstrap

Algorithm
1. Create schema
2. Upload image and calculate histograms
3. Add image and calculated features to the database
4. Search for similarity in saved images
5. Return a subset with the most similar according to a distance measure

The Tasks
Some required tasks for the
project.
1. Extract Features
2. Add Image to Database
3. Search through Images and
Compare Features
4. Return Similar Images

1. Extract Features
● Color Vector: CalcHist()
OpenCV method - HSV
● Texture Vector: LBP
(Local Binary Patterns)
Scıkıt-Image Lıbrary - GrayScale
● Shape Vector: Hu Moments
OpenCV method - GrayScale
Normalize all!
2. Add Image to DB
● Save image to local folder
● Get path of image
● Save path and features on
Database
→

3. Search through Images
● Concatenate vectors
● Calculate ChiSquare (x2
) distance
● Get results
4. Return Similar
● Sort Results
● Keep 8 best
● Present
→

Add Many Images
More Features
Annotations
Video
Audio
Ontology
Crawling
Future Work
Text-Based Retrieval
Image Segmentation

Resources
● PyImageSearch (http://www.pyimagesearch.com/)
● HanzraTech (http://hanzratech.in/2015/05/30/local-binary-patterns.html)
● Unsplash (https://unsplash.com/)

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