Morphological Algorithm for Color Objects Classification

Zaharescu, Eugen

doi:10.1109/bci.2009.17

Cited by 3 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence, the results obtained from the MSA with node weights will be assigned to the fine segmentation using mathematical morphology method. Morphological by dilation and closing operators, introduced by Zaharescu [44], will be used to extract the most contrasted structures and the corresponding size of the exudates regions. Both operators are controlled by a disc structuring element in order to find the region of interest (ROI) in the retinal images.…”

Section: Fine Segmentation Using Mathematical Morphologymentioning

confidence: 99%

Exudates Detection Using Morphology Mean Shift Algorithm in Retinal Images

Wisaeng

Sa-ngiamvibool

2019

IEEE Access

View full text Add to dashboard Cite

Exudates are a serious complication causing blindness in diabetic retinopathy patients. The main objective of this paper is to develop a novel method to detect exudates lesions in color retinal images by using a morphology mean shift algorithm. The proposed method start with a normalization of the retinal image, contrast enhancement, noise removal, and the localization of the OD. Then, a coarse segmentation method by using mean shift provides a set of exudates and non-exudates candidates. Finally, a classification using the mathematical morphology algorithm (MMA) procedure is applied in order to keep only exudates pixels. The optimal value parameters of the MMA will facilitate an increase of the accuracy results from the solely MSA method by 13.10%. Based on a comparison between the results and ground truth images, the proposed method obtained an average sensitivity, specificity, and accuracy of detecting exudates as 98.40%, 98.13%, and 98.35%, respectively.

show abstract

Section: Fine Segmentation Using Mathematical Morphologymentioning

confidence: 99%

Exudates Detection Using Morphology Mean Shift Algorithm in Retinal Images

Wisaeng

Sa-ngiamvibool

2019

IEEE Access

View full text Add to dashboard Cite

show abstract

Robust color texture retrieval method using co-occurrence matrix of pattern spectrums

Takei

Wada

2012

2012 IEEE 11th International Conference on Signal Processing

View full text Add to dashboard Cite

Color Image Indexing Using Mathematical Morphology

Zaharescu

2014

Analele Universitatii "Ovidius" Constanta - Seria Matematica

Self Cite

View full text Add to dashboard Cite

A mathematical morphology based approach for color image indexing is explored in this paper. Morphological signatures are powerful descriptions of the image content in the framework of mathematical morphology. A morphological signature (either a pattern spectrum or a differential morphological profile) is defined as a series of morphological operations (namely openings and closings) considering a predefined pattern called structuring element. For image indexing it is considered a morphological feature extraction algorithm which includes more complex morphological operators: i.e. color gradient, homotopic skeleton, Hit-or-Miss transform. In the end, illustrative application examples of the presented approach on real acquired images are also provided.

show abstract

Morphological Algorithm for Color Objects Classification

Cited by 3 publications

References 7 publications

Exudates Detection Using Morphology Mean Shift Algorithm in Retinal Images

Exudates Detection Using Morphology Mean Shift Algorithm in Retinal Images

Robust color texture retrieval method using co-occurrence matrix of pattern spectrums

Color Image Indexing Using Mathematical Morphology

Contact Info

Product

Resources

About