Ppt 1

SMARANIKA SAHU1ST SEM M.TECH(ETC)

KRUPAJAL ENGINEERING COLLGE,BBSR,ORISSA,INDIA

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Image mining is an extension of data mining to image domain.

Image mining deals with the extraction of image patterns from large collection of objects.

Image mining is the extraction of implicit knowledge, image data relationship or other patterns not explicitly stored in the images.

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Discovering image patterns that are significant in a given collection of objects.

To extract (i.e. searching and finding ) useful patterns from the large number of image data such as satellite images, medical images and digital photographs in the world wide web or any repository.

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Image mining needs expertise in: Computer Vision Image Processing Image Retrieval data Mining Machine Learning Database and Artificial Intelligence.

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Images in database

Preprocessing

Transformation and Feature Extraction MININ

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Interpretation and Evaluation

Knowledge

Focus of image mining is an extraction of patterns from large collection of images

BUTFocus of computer vision and Image processing technique is in understanding and/or extracting specific features from a single image.

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To determine how low-level pixel representation contained in a raw image or image sequence can be efficiently and effectively processed to identify high-level spatial objects and relationships.

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To conclude/detect flood or drought region from Remote sensing images.

To detect brain tumor from brain images.

Weather forecasting,Criminal Investigation(e.g. Face detection)

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Raw image data of database needs to be processed before used in image mining.

A good image mining system is expected to provide users with an effective access into the image repository and generation of knowledge and patterns underneath the images.

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Image Storage

Image Processing

Feature Extraction

Image Indexing

Image Retrieval

Knowledge Discovery

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Two types:Function-Driven image mining:

Focuses on the functionalities of different component modules in the organization of image mining system

Information-Driven image mining:Designed as a hierarchical

structure with special emphasis on the information needs at various level.

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Frequently used techniques used in image mining are:

Object recognitionImage Indexing and RetrievalImage Classification and Clustering

Association Rule MiningNeural Networks

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Image classification refers to the numerical analysis of various image features and organize data into categories.

Classification algorithms make use of two phases of processing:

Training Phase: Distinguishing properties of typical image features are isolated and based on these , a unique description of each classification category(training class) is created.

Testing Phase: The partitioned feature space are used to classify image feature.

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Image mining is of wide research area and our main focus will be on classification.

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