An integrated methodology for the detection and removal of cracks on digitized paintings is presented in this paper. The cracks are detected by thresholding the output of the morphological top-hat transform. Afterward, the thin dark brush strokes which have been misidentified as cracks are removed using either a median radial basis function neural network on hue and saturation data or a semi-automatic procedure based on region growing. Finally, crack filling using order statistics filters or controlled anisotropic diffusion is performed. The methodology has been shown to perform very well on digitized paintings suffering from cracks.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE :Digital Self-Interference Cancellation With Variable Fractional Delay FIR Filter for Full-Duplex Radios - 2018ABSTRACT:In full-duplex radios, delay alignment errors end in random mismatch between the self-interference
PROJECT TITLE :A Droop Measurement Built-in Self-Test Circuit for Digital Low-Dropout Regulators - 2018ABSTRACT:Today's highly integrated system-on-chips (SOCs) employ several integrated voltage regulators to realize higher power
PROJECT TITLE :Evolutionary Approach to Approximate Digital Circuits Design - 2017ABSTRACT:In approximate computing, the need of excellent functional behavior will be relaxed as a result of some applications are inherently error
PROJECT TITLE :A Fully Digital Front-End Architecture for ECG Acquisition System With 0.5 V Supply - 2017ABSTRACT:This paper presents a brand new power-economical electrocardiogram acquisition system that uses a fully digital
PROJECT TITLE :High-performance engineered gate transistor-based compact digital circuits - 2017ABSTRACT:A unique methodology for coming up with and realising compact digital circuits by engineering MOSFET gate electrode is proposed.

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry