Content Based Image Retrieval
Download as PPTX, PDF8 likes4,472 views
This document summarizes a seminar presentation on Content Based Image Retrieval (CBIR). CBIR allows users to search for digital images in large databases based on the images' visual contents like color, shape, and texture, rather than keywords. The seminar covers the inspiration for CBIR, different types of image retrieval, how CBIR works by extracting features from images, applications like crime prevention and biomedicine, advantages like efficient searching, and limitations like accuracy issues. The goal of CBIR research is to develop algorithms that can characterize and understand images like human vision.
Content Based Image Retrieval
- 1. ACADEMY OF TEHNOLOGY Subject Code - CS681 Seminar on : Content Based Image Retrieval(CBIR) ---Under the Guidance of • Prof. Sudipta Roy • Assistant Professor • Dept. of Computer Science • Adeconagar, Hoogly - 712121 ---By • Sourav Kar • B.Tech. CSE 6th Semester • Dept. of Computer Science • Adeconagar, Hoogly - 712121 Content Based Image Retrieval 1
- 2. Contents: • Inspiration • Types Of Image Retrieval • Introduction • How to Search Images • Color Image Variances • CBIR Working Process • Applications of CBIR • Advantages Of CBIR • Limitations / Disadvantages of CBIR • Conclusion • References Content Based Image Retrieval 2
- 3. Inspiration: • Digital image database growing rapidly in size • Professional needs – Logo Search • Difficulty in locating images on the web Content Based Image Retrieval 3 Types Of Image Retrieval There are two types of image retrieval process. Such as- • Text Based Image Retrieval • Content Based Image Retrieval Here we only discussed about the content based image retrieval system.
- 4. Introduction: • Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases. • "Content-based" means that the search will analyze the actual contents of the image. The term 'content' in this context might refer colors, shapes, textures, or any other information that can be derived form the image itself. Content Based Image Retrieval 4 How to search images ? 1.Color 2.Local Shape 3.Texture
- 5. Content Based Image Retrieval 5 Color: • Examining images based on the colors they contain is one of the most widely used techniques because it does not depend on image size or orientation. Shape: • Shape does not refer to the shape of an image but to the shape of a particular region that is being sought out. Texture: • Texture Measures Look for visuals patterns in images.
- 6. Content Based Image Retrieval 6 Color Images: • Problems with color variances Surface Orientation Camera Viewpoint Intensity of the Light
- 7. How CBIR works ? Content Based Image Retrieval 7
- 8. In Depth Of Feature Extraction: Content Based Image Retrieval 8 Depth Of Feedback:
- 9. Practical Example: Content Based Image Retrieval 9
- 10. Content Based Image Retrieval 10 Applications of CBIR: • Search for one specific image. • General browsing to make an interactive choice. • Search for a picture to go with a broad story or search to illustrate a document. • Example: Crime prevention (security filtering …), Biomedicine (X-ray, CT …) , Commerce (fashion) etc.
- 11. Advantages Of CBIR: • CBIR has become a very active area research for two major research communities, Database Management and Computer Vision. • Feature Extraction methods are easy, effective and less expensive. • Time require is less to find all those related image. • More than one related outcomes occur by only one search(If more than one equally likely image present in the database). Content Based Image Retrieval 11
- 12. Disadvantages: • We do not yet have a universally acceptable algorithmic means of characterizing human vision, more specifically in the context of image understanding. • Hence it is not surprising to see continuing efforts towards it, either building up on prior work or exploring novel directions. • Accuracy is not up to the mark. • Continuous filtering is needed for achieving accurate output. Content Based Image Retrieval 12
- 13. Content Based Image Retrieval 13 Conclusions: • CBIR is used to search a specific image from a large database. • CBIR makes interactive search of images from the database. • Until now CBIR is not the most accurate technique for finding desired outcomes. • This technique is still in research state for finding better and accurate output. • At present this technique is implemented by Google.
- 14. Content Based Image Retrieval 14 References: • http://en.wikipedia.org/wiki/Content-based_image_retrieval -Date: 26/4/16 • http://www.cs.washington.edu/homes/shapiro/cbir.html -Date: 26/4/16 • http://www.engineersgarage.com/contribution/content-based-image- retrieval-matlab-project -Date: 26/4/16
- 15. THANK YOU Content Based Image Retrieval 15