Pattern Recognition
Moment-preserving sharpening—a new approach to digital picture deblurring
Computer Vision, Graphics, and Image Processing
Moment-preserving curve detection
IEEE Transactions on Systems, Man and Cybernetics
Moment-preserving line detection
Pattern Recognition
Moment-preserving corner detection
Pattern Recognition
Pattern Recognition
Digital Picture Processing
A novel image thresholding method based on Parzen window estimate
Pattern Recognition
A hidden Markov model-based character extraction method
Pattern Recognition
| Hi-index | 14.98 |
A neural-network implementation of the moment-preserving technique, which is widely used for image processing, is proposed. The moment-preserving technique can be thought of as an information transformation method which groups the pixels of an image into classes. The variables in the so-called moment-preserving equations are determined iteratively by a recurrent neural network and a connectionist neural network which work cooperatively. Both of the networks are designed in such a way that the sum of square errors between the moments of the input image and those of the output version is minimized. The proposed neural network system is applied to automatic threshold selection. The experimental results show that the system can threshold images successfully. The performance of the method is compared with those of four other histogram-based multilevel threshold selection methods. The simulation results show that the proposed technique is at least as good as the other methods.