Analyzing and mining image databases

Berlage, Thomas

doi:10.1016/s1359-6446(05)03462-8

Cited by 11 publications

(7 citation statements)

References 58 publications

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“…Berlage distinguishes three segmentation approaches [6]: 1) Marker-based segmentation -Objects are represented by an area covered by a marker. The object to be detected is identified based on labelling the space within an image.…”

Section: B Object Recognitionmentioning

confidence: 99%

“…However, the field remains in its infancy and categorising into non-pre-defined classes is still an issue to be solved. The researched methods of categorising objects as described by [6], [8], [11] are:…”

Section: Image Classificationmentioning

confidence: 99%

“…Several compression formats (JPEG, MPEG 7, DICOM) store the meta data in one file with an image. According to [6]), this approach might result in difficulties with analysing images. Databases of such images are not the most suitable candidates for data mining, as they are not optimised for time-and memoryconsumption when performing image retrieval.…”

Section: A Storing Imagesmentioning

confidence: 99%

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Image Mining: Review and New Challenges

Zahradníková¹,

Duchovičová²,

Schreiber³

2015

ijacsa

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Abstract-Besides new technology, a huge volume of data in various form has been available for people. Image data represents a keystone of many research areas including medicine, forensic criminology, robotics and industrial automation, meteorology and geography as well as education. Therefore, obtaining specific information from image databases has become of great importance. Images as a special category of data differ from text data as in terms of their nature so in terms of storing and retrieving. Image Mining as a research field is an interdisciplinary area combining methodologies and knowledge of many branches including data mining, computer vision, image processing, image retrieval, statistics, recognition, machine learning, artificial intelligence etc. This review focuses researching the current image mining approaches and techniques aiming at widening the possibilities of facial image analysis. This paper aims at reviewing the current state of the IM as well as at describing challenges and identifying directions of the future research in the field.

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Section: B Object Recognitionmentioning

confidence: 99%

Section: Image Classificationmentioning

confidence: 99%

Section: A Storing Imagesmentioning

confidence: 99%

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Image Mining: Review and New Challenges

Zahradníková¹,

Duchovičová²,

Schreiber³

2015

ijacsa

View full text Add to dashboard Cite

show abstract

“…It serves to control and set up the instrument for image capture and provides tools for image analysis and data visualization (14,16,17). The software should also integrate into a database application to manage and store the large volume of data that an automated HCS imager can generate (14,16,17). The number and types of fluorescent probes in a sample will determine how many separate channels will need to be collected, and which excitation and emission filters are required.…”

Section: Imaging Platform Softwarementioning

confidence: 99%

“…The automated imaging platform software should also provide an integrated environment that supports visual data mining (10)(11)(12)17). The software should allow the user to inspect and interpret the multiparameter analysis results in the context of the images, the raw data, the experimental conditions and procedures 2.4 IMAGING PLATFORM SOFTWARE utilized.…”

Section: Imaging Platform Softwarementioning

confidence: 99%