Due to the advent of computer technology image-processing techniques have become increasingly important in a wide variety of applications. Image segmentation is a classic subject in the field of image processing and also is a hotspot and focus of image processing techniques. With the improvement of computer processing capabilities and the increased application of color image, the color image se...

Image segmentation is the task of associating pixels in an image with their respective object class labels. It has a wide range applications many industries including healthcare, transportation, robotics, fashion, home improvement, and tourism. Many deep learning-based approaches have been developed for image-level recognition pixel-level scene understanding-with latter requiring much denser an...

We are investigating techniques for producing textual summaries of time series data. Deep reasoning techniques have proven impractical because we lack perfect knowledge about users and their tasks. Data analysis techniques such as segmentation are more attractive, but they have been developed for data mining, not for communication. We examine how segmentation should be modified to make it suita...

Image segmentation is a crucial problem in image processing and can determine the final outcome of many image processing tasks. Lots of research has gone into segmentation of monotone images, however, recently more research has gone into segmenting colour images. Genetic algorithms have been shown to be a viable method to segment an image. The island model has been shown to be the most effectiv...

`Over-segmentation', `under-segmentation', `good results' and similar subjective terms appear frequently in the literature on range image segmentation. However, even though the need for standardized segmentation error metrics has been long recognized, no formal methodology for evaluating a range image segmentation has appeared. This paper describes a framework in which to carry out such an eval...

Partitioning of an image into several constituent components is called image segmentation. Myriad algorithms using different methods have been proposed for image segmentation. Many clustering algorithms and optimization techniques are also being used for segmentation of images. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. A...

Image segmentation is the process of partitioning an image into multiple segments, so as to change the representation of an image into something that is more meaningful and easier to analyze. Several general-purpose algorithms and techniques have been developed for image segmentation. This paper describes the different segmentation techniques used in the field of MRI Image Processing. This pape...

Image segmentation is the basic step in image Analysis and processing mechanism. The Image is partitioned into multiple segments so that a meaningful image is extracted out and then image is analyzed easily. Many techniques have been developed for the Image segmentation and there has been a constant growth in the research area of image segmentation and with this it has become more important to ...

Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In ...