Data mining involves automatically extracting knowledge from large data sets. For multimedia data like images, video and audio, data mining techniques are used to discover relationships between objects. Image mining techniques include object recognition, image retrieval, image indexing, image classification and clustering, and association rule mining. Image mining is used in applications like military reconnaissance, weather forecasting, criminal investigations and medical imaging.

1. Multi media

2. Data mining
Automatic Extraction of knowledge form a data warehouse
Is termed to be as data mining
Data mining is generally used in various fields here we are
gonna see about mining on Audio and video

3. Multi media data system
Generally, multimedia database systems stored and manage a large
collection of multimedia objects, such as image, video, audio and
hypertext data
Thus, in multimedia documents, knowledge discovery deals with non
structured information. For this reason we need tools for discovering
relationships between objects such as
Classifying images based on content
Extracting patterns in sounds
Categorizing speech and music

4. Image mining techniques
Object recognition
◦Can be referred to as a supervised labeling problem based on models of
known objects
◦Specifically, given a target image containing one or more objects and set of
labels corresponding to a set of models known to the system
Mainly image mining deals with
Image retrieval
Image indexing
Image classification and clustering
Association rule mining

5. Image Retrieval
Image mining requires that images be retrieved according to some required specifications
LEVEL 1
Comprises image retrieval by primitive features such as colors, shapes or location on the image
where the object is present
LEVEL 2
Image is retrieved based on logical features like type of objects given
LEVEL 3
Comprises image retrieval by abstract attributes, involving in high logical rasoning

6. Image Clustering
Image clustering is usually performed in the early stages of mining process
Clustering an image is based on it’s attributes color, shape texture etc..
These clustering techniques are used by google and bing’s image search pages
There are several algorithms for clustering an image such as
◦ Hierarchical clustering
◦ Partition based algorithm
◦ Near neighbor clustering
◦ Fuzzy clustering
◦ Evolutionary clustering

7. Association rules
This is applied to large image databases
There are two main approaches
◦Mine large collections of images alone
◦Mine form combined collections of image and associated alphanumeric data
Ex: If the upper part of picture is atleast 50%, then it’s a sky
The image can also be modeled as a transaction, assigned with an image ID
and features

8. Applications of image mining
• Military Reconnaissance
• Weather Forecasting
• Management of Earth’s Resources
• Forest Fires
• Criminal Investigation
• Medical Imaging
◦OCR
◦Face recognition systems

9. Conclusion
The image mining is an technology under existence and still
developed
Search engines use this mining for image searches
Currently ROBOs are made to identify the patterns in an image as
humans do

10. Conclusion
The image mining is an technology under existence and still
developed
Search engines use this mining for image searches
Currently ROBOs are made to identify the patterns in an image as
humans do