Manish Kumar Bajpai

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
Discrimination between texture edges and geometrical edges is very difficult in low contrast images. Satellite images are low contrast images. It is important to extract the edges that are not clearly visible in case of Satellite images. The present work encompasses a new edge detection algorithm using newly constructed differentiator. Chebyshev polynomial(More)
Computer-aided detection systems play an important role for the detection of breast abnormalities using mammograms. Global segmentation of mass in mammograms is a complex process due to low contrast mammogram images, irregular shape of mass, speculated margins, and the presence of intensity variations of pixels. This work presents a new approach for mass(More)
The present study introduces an efficient algorithm for automatic segmentation and detection of mass present in the mammograms. The problem of over and under-segmentation of low-contrast mammographic images has been solved by applying preprocessing on original mammograms. Subtraction operation performed between enhanced and enhanced inverted mammogram(More)
Automatic segmentation of abnormal region is a crucial task in computer aided detection system using mammograms. In this work an automatic abnormality detection algorithm using mammographic images is proposed. In the preprocessing step, partial differential equation based variational level set method is employed for breast region extraction. The evolution(More)
A discrete time modeled fractional order differentiator has been designed for estimating the fractional order derivative of contaminated signal. The proposed approach uses Chebyshev polynomial based approximation. Riemann-Liouville fractional order derivative definition has been used for design of fractional order Savitzky-Golay differentiator. Proposed(More)
  • 1