Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

Abstract

Although the rapid development in reverse engineering techniques, 3D laser scanners can be considered the modern technology used to digitize the 3D objects, but some troubles may be associate this process due to the environmental noises and limitation of the used scanners. So, in the present paper a data pre-processing algorithm has been proposed to obtain the necessary geometric features and mathematical representation of scanned object from its point cloud which obtained using 3D laser scanner (Matter and Form) through isolating the noised points. The proposed algorithm based on continuous calculations of chord angle between each adjacent pair of points in point cloud. A MATLAB program has been built t

Most systems are intelligent and the industrial world is moving now towards
technology. Most industrial systems are now computerized and offer a high speed.
However, Face recognition is a biometric system that can identify people from their
faces. For few number of people to be identified, it can be considered as a fast
system. When the number of people grew to be bigger, the system cannot be adopted
in a real-time application because its speed will degrade along with its accuracy.
However, the accuracy can be enhanced using pre-processing techniques but the
time delay is still a challenge. A series of experiments had been done on AT&TORL
database images using Enhanced Face Recognition System (EFRS) that is

Feature extraction provide a quick process for extracting object from remote sensing data (images) saving time to urban planner or GIS user from digitizing hundreds of time by hand. In the present work manual, rule based, and classification methods have been applied. And using an object- based approach to classify imagery. From the result, we obtained that each method is suitable for extraction depending on the properties of the object, for example, manual method is convenient for object, which is clear, and have sufficient area, also choosing scale and merge level have significant effect on the classification process and the accuracy of object extraction. Also from the results the rule-based method is more suitable method for extracting

In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

Merging images is one of the most important technologies in remote sensing applications and geographic information systems. In this study, a simulation process using a camera for fused images by using resizing image for interpolation methods (nearest, bilinear and bicubic). Statistical techniques have been used as an efficient merging technique in the images integration process employing different models namely Local Mean Matching (LMM) and Regression Variable Substitution (RVS), and apply spatial frequency techniques include high pass filter additive method (HPFA).  Thus, in the current research, statistical measures have been used to check the quality of the merged images. This has been carried out by calculating the correlation a

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.