Parallel algorithm for gray-scale image segmentation
نویسنده
چکیده
One of the classic algorithms of mathematical morphology is the image segmentation algorithm of Rosenfeld-Pfaltz. This algorithm in its "sequential" form, seeks to mark with a common label all connected pixels in an image, where the connectivity actually used in practice is 4-connectivity or 8-connectivity. The sequential Rosenfeld-Pfaltz algorithm (RS Algorithm) algorithm was presented for binary images; Cohen has previously presented a one-pass modification to the RS algorithm, and extended the algorithm to gray-scale. The RS algorithm is not simple to parallelise in principle, as pixels in a connected subregion may be connected only via a chain of connected pixels in several other sub-regions. We present here a parallelisable algorithm for segmenting into regions images of multiple gray-scale, based on the one-pass algorithm.
منابع مشابه
High Performance Implementation of Fuzzy C-Means and Watershed Algorithms for MRI Segmentation
Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...
متن کاملHigh Performance Implementation of Fuzzy C-Means and Watershed Algorithms for MRI Segmentation
Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...
متن کاملA comparative performance of gray level image thresholding using normalized graph cut based standard S membership function
In this research paper, we use a normalized graph cut measure as a thresholding principle to separate an object from the background based on the standard S membership function. The implementation of the proposed algorithm known as fuzzy normalized graph cut method. This proposed algorithm compared with the fuzzy entropy method [25], Kittler [11], Rosin [21], Sauvola [23] and Wolf [33] method. M...
متن کاملExtraction and 3D Segmentation of Tumors-Based Unsupervised Clustering Techniques in Medical Images
Introduction The diagnosis and separation of cancerous tumors in medical images require accuracy, experience, and time, and it has always posed itself as a major challenge to the radiologists and physicians. Materials and Methods We Received 290 medical images composed of 120 mammographic images, LJPEG format, scanned in gray-scale with 50 microns size, 110 MRI images including of T1-Wighted, T...
متن کاملFOPWA: An Optimized Parallel Algorithm of Watershed Transform for Image Segmentation
Watershed segmentation/transform is a classical method for image segmentation in gray scale mathematical morphology. Nevertheless watershed algorithm has strong recursive nature, so straightforward parallel one has very low efficiency. Firstly, the advantages and disadvantages of some existing parallel algorithms are analyzed. Secondly, a Further Optimized Parallel Watershed Algorithm (FOPWA) i...
متن کامل