Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is efficient, has very few free parameters to tune, and the authors show how to tune the few remaining parameters. Results show that the method reliably aligns various datasets including two facial datasets and two medical datasets of prostate and brain MRI images and demonstrates efficiency in terms of performance and a reduction of the computational cost.
Uncompressed form of the digital images are needed a very large storage capacity amount, as a consequence requires large communication bandwidth for data transmission over the network. Image compression techniques not only minimize the image storage space but also preserve the quality of image. This paper reveal image compression technique which uses distinct image coding scheme based on wavelet transform that combined effective types of compression algorithms for further compression. EZW and SPIHT algorithms are types of significant compression techniques that obtainable for lossy image compression algorithms. The EZW coding is a worthwhile and simple efficient algorithm. SPIHT is an most powerful technique that utilize for image
... Show MoreIn this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.
Lowpass spatial filters are adopted to match the noise statistics of the degradation seeking
good quality smoothed images. This study imply different size and shape of smoothing
windows. The study shows that using a window square frame shape gives good quality
smoothing and at the same time preserving a certain level of high frequency components in
comparsion with standard smoothing filters.
The wavelet transform has become a useful computational tool for a variety of signal and image processing applications.
The aim of this paper is to present the comparative study of various wavelet filters. Eleven different wavelet filters (Haar, Mallat, Symlets, Integer, Conflict, Daubechi 1, Daubechi 2, Daubechi 4, Daubechi 7, Daubechi 12 and Daubechi 20) are used to compress seven true color images of 256x256 as a samples. Image quality, parameters such as peak signal-to-noise ratio (PSNR), normalized mean square error have been used to evaluate the performance of wavelet filters.
In our work PSNR is used as a measure of accuracy performanc
... Show MoreThe computer vision branch of the artificial intelligence field is concerned with
developing algorithms for analyzing image content. Data may be compressed by
reducing the redundancy in the original data, but this makes the data have more
errors. In this paper image compression based on a new method that has been
created for image compression which is called Five Modulus Method (FMM). The
new method consists of converting each pixel value in an (4x4, 8×8,16x16) block
into a multiple of 5 for each of the R, G and B arrays. After that, the new values
could be divided by 5 to get new values which are 6-bit length for each pixel and it
is less in storage space than the original value which is 8-bits.
This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
Platelet‐rich fibrin (PRF) has been widely used in regenerative dentistry due to many growth factors produced. Periostin, a matricellular protein, is a reliable marker for tissue regeneration. Periostin is part of the cellular matrix and regulates bone homeostasis. This study aims to explore the efficacy of PRF in improvement of the clinical periodontal parameters as an adjunct to the scaling and root planing and to evaluate periostin level in gingival crevicular fluid (GCF) at baseline, 1‐ and 3‐month recall visits. Fourteen periodontitis patients who met the inclusion criteria were recruited in this study. Two contralateral periodontal pockets with 4–6 mm in depth in each patient were sel
The impact of smoking on human health is remarkable and can lead to death. This research was performed to test the effects of cigarette smoking on some parameters that are considered as signs of critical problems in human body. The study was carried out on fifty Iraqi male smokers in Baghdad city, who smoked at least 10 cigarettes per day for at least 15 years. The group includes 25 male smokers with an age range of 20 -55 years and 25 male non-smokers who were collected with the same range of age for statistical comparison. The results of the study revealed significant increases in blood parameters, including hemoglobin (Hb, 16.0917 (g/dl) , packed cell volume (PCV, 49.2%), red blood cells (RBC, 5.4763 X1012/L), white blood cell (WBC, 1
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