Interactive Retrieval of Color Images

Worring, Marcel; Gevers, Theo

doi:10.1142/s0219467801000244

Cited by 11 publications

(2 citation statements)

References 34 publications

(38 reference statements)

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“…The colour histogram is a method for describing the colour content of an image: it counts the number of occurrences of each colour in an image [14]. For a given RGB image, let L be the intensity levels in the range [0, 1, 2, …, L-1].…”

Section: Image Segmentationmentioning

confidence: 99%

Color space influence on ANN skin lesion classification using statistics texture feature

Damian

Moldovanu

Moraru

2021

Ann_UGAL_Math_Phys_Mec

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This study aims to investigate the ability of an artificial neural network to differentiate between malign and benign skin lesions based on two statistics terms and for RGB (R red, G green, B blue) and YIQ (Y luminance, and I and Q chromatic differences) color spaces. The targeted statistics texture features are skewness (S) and kurtosis (K) which are extracted from the histograms of each color channel corresponding to the color spaces and for the two classes of lesions: nevi and melanomas. The extracted data is used to train the Feed-Forward Back Propagation Networks (FFBPNs). The number of neurons in the hidden layer varies: it can be 8, 16, 24, or 32. The results indicate skewness features computed for the red channel in the RGB color space as the best choice to reach the goal of our study. The reported result shows the advantages of monochrome channels representation for skin lesions diagnosis.

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Section: Image Segmentationmentioning

confidence: 99%

Color space influence on ANN skin lesion classification using statistics texture feature

Damian

Moldovanu

Moraru

2021

Ann_UGAL_Math_Phys_Mec

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“…Most of the multimedia retrieval techniques focus on the retrieval of single modality data, such as images [1,2,3] and text documents [4,5]. Some recent works have focused on cross-media retrieval where the query examples and the query results have different modalities [6,7,8,9].…”

Section: Introductionmentioning

confidence: 99%

Search and retrieval of multi-modal data associated with image-parts

Pourian

Karthikeyan

Manjunath

2015

2015 IEEE International Conference on Image Processing (ICIP)

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We present a novel framework for querying multi-modal data from a heterogeneous database containing images, textual tags, and GPS coordinates. We construct a bi-layer graph structure using localized image-parts and associated GPS locations and textual tags from the database. The first layer graphs capture similar data points from a single modality using a spectral clustering algorithm. The second layer of our multi-modal network allows one to integrate the relationships between clusters of different modalities. The proposed network model enables us to use flexible multi-modal queries on the database.

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