A Gabor-filtering method for describing textural features

is proposed, which applies the physical properties of a probability

wave to probability transformation, and computes

textural features

2) An adaptive strategy for feature and filter selection, and

feature weighting, is proposed, which utilizes a user’s relevance

feedback to reduce the redundancy in the representation

and incorporate the user’s information needs in image

retri

3) Integrating both schemes (the Gabor-filtering method and

the adaptive strategy) for content-based mammogram retri

is suggested-A Gabor-filtering method for describing textural features

is proposed, which applies the physical properties of a probability

wave to probability transformation, and computes

textural features

2) An adaptive strategy for feature and filter selection, and

feature weighting, is proposed, which utilizes a user’s relevance

feedback to reduce the redundancy in the representation

and incorporate the user’s information needs in image

retri　

3) Integrating both schemes (the Gabor-filtering method and

the adaptive strategy) for content-based mammogram retri

is suggested