Thresholding color video images is challenging because of the low spatial resolution and the complex backgrounds. This paper investigates the issue of thresholding these images by reducing the number of colors in order to improve automated text detection and recognition. An unsupervised thresholding approach is presented which reduces the background complexity while retaining the important text...

electrocardiogram (ecg) is one of the most common biological signals which plays a significant role in diagnosis of heart diseases. one of the most important parts of ecg signal processing is interpretation of qrs complex and obtaining its characteristics. r wave is one of the most important sections of this complex which has an essential role in diagnosis of heart rhythm irregularities and als...

The major drawback of watershed transformation is over-segmentation. It also has a significant advantage: very good edge extraction. Thresholding methods usually utilize only global information such as an image histogram; however, they have the ability to group pixels into clusters by their value. The method presented in this paper combines the advantages of watershed segmentation and multileve...

This paper about to reduce the noise by Adaptive time-frequency Block Thresholding procedure using discrete wavelet transform to achieve better SNR of the audio signal. Discrete-wavelet transforms based algorithms are used for audio signal denoising. The resulting algorithm is robust to variations of signal structures such as short transients and long harmonics. Analysis is done on noisy speech...

The paper presents some aspects of the (gray level) image binarization methods used in artificial vision systems. It is introduced a new approach of gray level image binarization for artificial vision systems dedicated to industrial automation – temporal thresholding. In the first part of the paper are extracted some limitations of using the global optimum thresholding in gray level image binar...

Noise reduction has been a traditional problem in image processing. Recent wavelet thresholding based denoising methods proved promising, since they are capable of suppressing noise while maintaining the high frequency signal details. However, the local space-scale information of the image is not adaptively considered by standard wavelet thresholding methods. In this paper, a new type of thresh...

Beam thresholding is a widely-used pruning approach in decoding algorithms of statistical machine translation. In this paper, we propose two variations on the conventional beam thresholding, both of which speed up the decoding without degrading BLEU score. The first variation is the dynamic beam thresholding, in which the beam threshold varies with the length of source sequences covered by hypo...

Several algorithms have previously been proposed for improving the thresholding of degraded document images. No algorithm can solve all types of problems, but some algorithms are better than others for specific situations. This article reviews global binarization algorithms for improving degraded document images, thus indicating their differences and similarities, and also their advantages and ...

Aim of this paper is reformulation of global image thresholding problem as a well-founded statistical method known as change-point detection (CPD) problem. Our proposed CPD thresholding algorithm does not assume any prior statistical distribution of background and object grey levels. Further, this method is less influenced by an outlier due to our judicious derivation of a robust criterion func...