Photo Album Generator

Project Title

Photo Album Generator

Project Area of Specialization Augmented and Virtual RealityProject Summary

In our project of  photo album generator application, we will use local binary pattern and hog features to extract the features of query image and database images and then compared the extracted features of query and database images and calculated the Euclidean distance, then those database images that have minimum Euclidean distance with query image are retrieved. In this process of image retrieval, the maximum accuracy we will achieve comes to us in the form of no of images.

Project Objectives

Our project will produce a desktop application by using the image contents. We provide searching based on image content rather than their meta-information such as the tags on the image, any associated information, or the keywords. These substances comprise of shading, shape, surface, and example to look through client required picture from enormous scale picture database as per client's inquiry picture.

Project Implementation Method

a methodology is proposed which recovers comparable images from the database utilizing images as a query. This approach utilizes low-level aspects of images for CBIR. The goal of this work is to make image recovery productive, quick, and less mind-boggling. To accomplish this target, two techniques are utilized to extract the surface features and object detection. The fundamental thought of the proposed work in this paper is to extract the surface and object detection of images. HOG includes descriptor is successful to represent objects and is broadly utilized in person and face discovery. The surface is an attribute that demonstrates the spatial arrangement of the pixel's gray level in a region or picture.An incremental model is used to develop this project, in which the whole requirement is divided into various modules. Each module is further passing through easily managed phases of requirement, design, implementation, and testing until the product is finished.

Modules of the project:

• SELECT IMAGE
• BROWSE QUERY
• EXTRACT FEATURES
• SEARCH IMAGES
• OUTPUT FOLDER
• CLOSE WINDOW

These modules will be implement accordingly 

Benefits of the Project

.•Generates working software quickly and early during the software life cycle.

•More flexible

•Less costly to change scope and requirements.

•Easier to test and debug during a smaller iteration.

• Easier to manage risk because risky pieces are identified and handled during its iteration.

•Each iteration is an easily managed milestone.

•It partitions the project into chunks.

•It creates a functional module early.

•If one phase is no available, it does not postpone the project.

• Content-Based Image Retrieval (CBIR) has become a very active research area.

• Feature Extraction methods are effective and less expensive in terms of competency.

  Most related outcomes occur via search using Content-Based Image Retrieval (CBIR).

Technical Details of Final Deliverable

We have to implement all the algorithums to reach the desired project. Basically we have diffrent intangible modules. and as we are working on MATLAB software we have to place every code in diffrent push button for working. Here is some algorithums and code to be implemented.

CBIR (Contant based image retrival)

CBIR Threshold

 Feature Vector 

HOG (as descriptor)

LBP (local binary pattern) as descriptor

Final Deliverable of the Project Software SystemCore Industry MediaOther Industries IT Core Technology OthersOther Technologies Augmented & Virtual RealitySustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	8000
printing paper Paper	Miscellaneous	4	2000	8000