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This paper introduces an automated image processing procedure capable of processing complementary deoxyribonucleic acid (cDNA) microarray images. Microarray data is contaminated by noise and suffers from broken edges and visual artifacts. Without the utilization of a filter, subsequent tasks such as spot identification and gene expression determination(More)
The rapid growth of image archives increases the need for efficient and fast tools that can retrieve and search through large amount of visual data. In this paper we propose an efficient method of extracting the image color content, which serves as an image digital signature, allowing to efficiently index and retrieve the content of large, heterogeneous(More)
This paper presents a novel filtering framework capable of processing cDNA microarray images. The proposed two-component adaptive vector filters integrate well-known concepts from the areas of fuzzy set theory, nonlinear filtering, multidimensional scaling and robust order-statistics. By appropriately setting the weighting coefficients in a generalized(More)
In this paper, a class of weighted vector directional filters (WVDFs) based on the selection of the output sample from the multichannel input set is analyzed and optimized. The WVDF output minimizes the sum of weighted angular distances to other input samples from the filtering window. Dependent on the weighting coefficients, the class of the WVDFs can be(More)