Hidden Markov models are well-known methods for image processing. They are used in many areas where 1D data are processed. In the case of 2D data, there appear some problems with application HMM. There are some solutions, but they convert input observation from 2D to 1D, or create parallel pseudo 2D HMM, which is set of 1D HMMs in fact. This paper describes authentic 2D HMM with two-dimensional...

One-dimensional (1D) kinematic, force, and EMG trajectories are often analyzed using zero-dimensional (0D) metrics like local extrema. Recently whole-trajectory 1D methods have emerged in the literature as alternatives. Since 0D and 1D methods can yield qualitatively different results, the two approaches may appear to be theoretically distinct. The purposes of this paper were (a) to clarify tha...

We generalize the concept of quasiparticle for one-dimensional (1D) interacting electronic systems. The ↑ and ↓ quasiparticles recombine the pseudoparticle colors c and s (charge and spin at zero magnetic field) and are constituted by one manypseudoparticle topological momenton and one or two pseudoparticles. These excitations cannot be separated. We consider the case of the Hubbard chain. We s...

Multi-symbology barcode location is a practical and challenging issue. Image-based barcode recognition techniques are robust and extendable approaches for reading versatile one-dimensional (1D) and two-dimensional (2D) barcodes. Most methods may work for a single 1D or 2D barcode or rely on a unique pattern to locate a single 1D or 2D barcode. This work proposes a general localization framework...

In this paper, we present a novel integral transform known as the one-dimensional quaternion quadratic-phase Fourier (1D-QQPFT). We first define (1D-QQPFT) of integrable (and square integrable) functions on R. Later on, show that 1D-QQPFT satisfies all respective properties such inversion formula, linearity, Moyal’s convolution theorem, correlation theorem and uncertainty principle. Moreover, u...