Some new 3-substituted-4-amino-5-mercapto-4(H)-1,2,4-triazoles as nonsteroidal antiinflammatory agents

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An augmented image gradients based supervised regression technique for iris center localization

This paper describes a robust and accurate technique for iris center localization by combining supervised regression based approach and image gradients. The proposed work consist of two stages. The first stage comprises regression approach which is based upon learning of local binary features to detect the periocular regions. In the second stage, image gradients were applied to the extracted eye patch regions to detect the accurate iris centers. The proposed augmented image gradients based supervised regression approach tested on the two publicly available challenging datasets show good accuracy. The results proved that supervised regression technique when augmented with image gradients approach improved the accuracy of iris center detection on the face image acquired under unconstraint conditions. The outcome of the proposed work suggests that by augmenting effective unsupervised techniques such as image gradients improves the accuracy and robustness of the supervised approaches used for face alignment applications. This work may be extended towards the development of accurate and fast eye gaze tracking systems

An augmented image gradients based supervised regression technique for iris center localization

This paper describes a robust and accurate technique for iris center localization by combining supervised regression based approach and image gradients. The proposed work consist of two stages. The first stage comprises regression approach which is based upon learning of local binary features to detect the periocular regions. In the second stage, image gradients were applied to the extracted eye patch regions to detect the accurate iris centers. The proposed augmented image gradients based supervised regression approach tested on the two publicly available challenging datasets show good accuracy. The results proved that supervised regression technique when augmented with image gradients approach improved the accuracy of iris center detection on the face image acquired under unconstraint conditions. The outcome of the proposed work suggests that by augmenting effective unsupervised techniques such as image gradients improves the accuracy and robustness of the supervised approaches used for face alignment applications. This work may be extended towards the development of accurate and fast eye gaze tracking systems

An Accurate and Simple Approach to Detect Eye Centers in Low Resolution Face Images

This paper introduces a new approach for accurate eye center localization based upon optimized image gradients algorithm. The proposed approach requires pre-fetched feature descriptors to detect the accurate iris centers amongst the possible eye center candidates computed by image gradients over the face image data-set. The results of the proposed algorithm for detecting eye, iris, and iris centers over the test set images of publicly available low resolution and challenging data-set show an accuracy percentage of 98.9, 95.7, and 89.2, respectively. The comparison results obtained by the proposed approach were at par with the state-of-the-art techniques involving complex calculations and training requirements. So, the superior performance and outcome of the proposed approach show the usefulness of optimizing the results of simple image gradients by pre-fetched Scale Invariant Feature Transform feature descriptors in detecting iris centers under unconstrained environments. The proposed approach may be useful for the development of real-time eye gaze tracking application with improved robustness and accuracy

Eye gaze tracking based directional control interface for interactive applications

This paper proposes an unobtrusive and calibration-free framework towards eye gaze tracking based interactive directional control interface for desktop environment using simple webcam under unconstrained settings. The proposed eye gaze tracking involved hybrid approach designed by combining two different techniques based upon both supervised and unsupervised methods wherein the unsupervised image gradients method computes the iris centers over the eye regions extracted by the supervised regression based algorithm. Experiments performed by the proposed hybrid approach to detect eye regions along with iris centers over challenging face image datasets exhibited exciting results. Similar approach for eye gaze tracking worked well in real-time by using a simple web camera. Further, PC based interactive directional control interface based upon iris position has been designed that works without needing any prior calibrations unlike other Infrared illumination based eye trackers. The proposed work may be useful to the people with full body motor disabilities, who need interactive and unobtrusive eye gaze control based applications to live independently

Influence on Color Attributes with Time due to Variations in Temperature Conditions

The effects of time and temperature over the color of freshly brewed Indian tea liquor using spectrophotometer were evaluated. The study suggests that after brewing, the tea samples undergo a color change which was measured in CIE L*a*b* color model. To find out the temperature effects, the experiment was done under two conditions i.e. normal cooling and imposed cooling of the sample to room temperature immediately after brewing. Change in the color was found less prominent in the latter case and it is concluded that the color changes rapidly after brewing and can pose difficulty in quality assessment of tea samples by tea tasters during visual inspection, if time and temperature are not taken into accoun