Image segmentation is a challenging research area in computer vision, image processing, and computer graphics. Interactive image segmentation is one important research branch of image segmentation, which has been applied in many areas such as medical imaging, movie industry, object tracking and sports. In this master’s thesis, a novel image segmentation method has been developed. This segmentat...

A PCA based gait segmentation method is proposed. Background images are used for PCA training. PCA reconstruction, recursive error compensation and single threshold based method is put forward for gait segmentation. Single threshold based method has the same gait segmentation ability as classical adaptive threshold based method, and the former is faster in implementation than the later. Propose...

Accurate image segmentation is important for many image, video and computer vision applications. Over the last few decades, many image segmentation methods have been proposed. However, the results of these segmentation methods are usually evaluated only visually, qualitatively, or indirectly by the effectiveness of the segmentation on the subsequent processing steps. Such methods are either sub...

In this paper we present our system for human-in-theloop video object segmentation. The backbone of our system is a method for one-shot video object segmentation [3]. While fast, this method requires an accurate pixel-level segmentation of one (or several) frames as input. As manually annotating such a segmentation is impractical, we propose a deep interactive image segmentation method, that ca...

In this paper, a modified segmentation algorithm for printed Farsi words is presented. This algorithm is based on a previous work by Azmi that uses the conditional labeling of the upper contour to find the segmentation points. The main objective is to improve the segmentation results for low quality prints. To achieve this, various modifications on local baseline detection, contour labeling an...

Automatic segmentation and detection of brain tumor is a notoriously complicated issue in Magnetic Resonance Image. The similar state-of-art segmentation methods and techniques are limited for the detection of tumor in multimodal brain MRI. Thus this work deals about the accurate segmentation and detection of tumor in multimodal brain MRI and this research work is focused to improve automatic s...