Finger vein extraction and recognition hold significance in various applications due to the unique and reliable nature of finger vein patterns. While recently finger vein recognition has gained popularity, there are s...Finger vein extraction and recognition hold significance in various applications due to the unique and reliable nature of finger vein patterns. While recently finger vein recognition has gained popularity, there are still challenges associated with extracting and processing finger vein patterns related to image quality, positioning and alignment, skin conditions, security concerns and processing techniques applied. In this paper, a method for robust segmentation of line patterns in strongly blurred images is presented and evaluated in vessel network extraction from infrared images of human fingers. In a four-step process: local normalization of brightness, image enhancement, segmentation and cleaning were involved. A novel image enhancement method was used to re-establish the line patterns from the brightness sum of the independent close-form solutions of the adopted optimization criterion derived in small windows. In the proposed method, the computational resources were reduced significantly compared to the solution derived when the whole image was processed. In the enhanced image, where the concave structures have been sufficiently emphasized, accurate detection of line patterns was obtained by local entropy thresholding. Typical segmentation errors appearing in the binary image were removed using morphological dilation with a line structuring element and morphological filtering with a majority filter to eliminate isolated blobs. The proposed method performs accurate detection of the vessel network in human finger infrared images, as the experimental results show, applied both in real and artificial images and can readily be applied in many image enhancement and segmentation applications.展开更多
Liberalized electricity markets,smart grids and high penetration of renewable energy sources(RESs)led to the development of novel markets,whose objective is the harmonization between production and demand,usually note...Liberalized electricity markets,smart grids and high penetration of renewable energy sources(RESs)led to the development of novel markets,whose objective is the harmonization between production and demand,usually noted as real time of flexibility markets.This necessitates the development of novel pricing schemes able to allow energy service providers(ESPs)to maximize their aggregated profits from the traditional markets(trading between wholesale/day-ahead and retail markets)and the innovative flexibility markets.In the same time,ESPs have to offer their end users(consumers)competitive(low cost)energy services.In this context,novel pricing schemes must act,among others,as automated demand side management(DSM)techniques that are able to trigger the desired behavioral changes according to the flexibility market prices in energy consumption curves(ECCs)of the consumers.Energy pricing schemes proposed so far,e.g.realtime pricing,interact in an efficient way with wholesale market.But they do not provide consumers with strong enough financial incentives to modify their energy consumption habits towards energy cost curtailment.Thus,they do not interact efficiently with flexibility markets.Therefore,we develop a flexibility real-time pricing(FRTP)scheme,which offers a dynamically adjustable level of financial incentives to participating users by fairly rewarding the ones that make desirable behavioral changes in their ECCs.Performance evaluation results demonstrate that the proposed FRTP is able to offer a 15%–30%more attractive trade-off between the stacked profits of ESPs,i.e.the sum of the profits from retail and flexibility markets,and the satisfaction of consumers.展开更多
文摘Finger vein extraction and recognition hold significance in various applications due to the unique and reliable nature of finger vein patterns. While recently finger vein recognition has gained popularity, there are still challenges associated with extracting and processing finger vein patterns related to image quality, positioning and alignment, skin conditions, security concerns and processing techniques applied. In this paper, a method for robust segmentation of line patterns in strongly blurred images is presented and evaluated in vessel network extraction from infrared images of human fingers. In a four-step process: local normalization of brightness, image enhancement, segmentation and cleaning were involved. A novel image enhancement method was used to re-establish the line patterns from the brightness sum of the independent close-form solutions of the adopted optimization criterion derived in small windows. In the proposed method, the computational resources were reduced significantly compared to the solution derived when the whole image was processed. In the enhanced image, where the concave structures have been sufficiently emphasized, accurate detection of line patterns was obtained by local entropy thresholding. Typical segmentation errors appearing in the binary image were removed using morphological dilation with a line structuring element and morphological filtering with a majority filter to eliminate isolated blobs. The proposed method performs accurate detection of the vessel network in human finger infrared images, as the experimental results show, applied both in real and artificial images and can readily be applied in many image enhancement and segmentation applications.
基金funding from the European Union’s Horizon 2020 Research and Innovation Programme(No.731767)in the context of the SOCIALENERGY project.
文摘Liberalized electricity markets,smart grids and high penetration of renewable energy sources(RESs)led to the development of novel markets,whose objective is the harmonization between production and demand,usually noted as real time of flexibility markets.This necessitates the development of novel pricing schemes able to allow energy service providers(ESPs)to maximize their aggregated profits from the traditional markets(trading between wholesale/day-ahead and retail markets)and the innovative flexibility markets.In the same time,ESPs have to offer their end users(consumers)competitive(low cost)energy services.In this context,novel pricing schemes must act,among others,as automated demand side management(DSM)techniques that are able to trigger the desired behavioral changes according to the flexibility market prices in energy consumption curves(ECCs)of the consumers.Energy pricing schemes proposed so far,e.g.realtime pricing,interact in an efficient way with wholesale market.But they do not provide consumers with strong enough financial incentives to modify their energy consumption habits towards energy cost curtailment.Thus,they do not interact efficiently with flexibility markets.Therefore,we develop a flexibility real-time pricing(FRTP)scheme,which offers a dynamically adjustable level of financial incentives to participating users by fairly rewarding the ones that make desirable behavioral changes in their ECCs.Performance evaluation results demonstrate that the proposed FRTP is able to offer a 15%–30%more attractive trade-off between the stacked profits of ESPs,i.e.the sum of the profits from retail and flexibility markets,and the satisfaction of consumers.
