scholarly journals Computer Assistive Palm Reader

2021 ◽  
Vol 9 (VII) ◽  
pp. 2461-2470
Author(s):  
Abhinav Kumar Pathak
Keyword(s):  
Image Processing ◽  
Morphological Operations ◽  
Prediction System ◽  
Decision Tree Classifier ◽  
Processing Application ◽  
Image Processing Application ◽  
Tree Classifier ◽  
Line Patterns ◽  
Principal Lines ◽  
Detection And Recognition

Palmistry, also known as palm reading or hand prediction, is the study of a person's personality, fortune, and future by examining his or her hands. Chiromancy is another name for it. Palmistry encompasses not just the reading of one's hand or palm, but also the reading of one's arm, finger, and fingernail. This system shows a digital image processing application that can be used in palmistry to predict people's personalities or future lives. Based on edge detection and recognition, a palmistry prediction system has been created. This developed system uses morphological operations as well. The system uses a decision tree classifier algorithm to identify specific features in the input images and extract principal lines from a human palm image. The most important line patterns in palmistry are summarised and used as models for fortune-telling palm reading. The model predicts a person's personality and displays the predictions based on palmistry knowledge and date of birth.

DFOG-Image Processing Application for Real-Time Defogging

2020 ◽  
Author(s):  
Indiketiya I.H.O.H ◽  
Kulasekara K.M.R.A ◽  
J.M. Thomas ◽  
Ishara Gamage ◽  
Thusithanjana Thilakarathna
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Processing Application ◽  
Image Processing Application

Formulation of Fractional Derivative-Based De-Hazing Algorithm and Implementation on Mobile-Embedded Devices

2019 ◽  
Vol 19 (01) ◽  
pp. 1950003
Author(s):  
Uche A. Nnolim
Keyword(s):  
Image Processing ◽  
Fractional Derivative ◽  
Mobile Devices ◽  
Fractional Order ◽  
Spatial Filter ◽  
Embedded Devices ◽  
Processing Application ◽  
Fractional Order Calculus ◽  
Image Processing Application ◽  
Logarithmic Image Processing

This paper presents the modification of a previously developed algorithm using fractional order calculus and its implementation on mobile-embedded devices such as smartphones. The system performs enhancement on three categories of images such as those exhibiting uneven illumination, faded features/colors and hazy appearance. The key contributions include the simplified scheme for illumination correction, contrast enhancement and de-hazing using fractional derivative-based spatial filter kernels. These are achieved without resorting to logarithmic image processing, histogram-based statistics and complex de-hazing techniques employed by conventional algorithms. The simplified structure enables ease of implementation of the algorithm on mobile devices as an image processing application. Results indicate that the fractional order version of the algorithm yields good results relative to the integer order version and other algorithms from the literature.

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