Threshold segmentation and Complementary Similarity Measure plays an important role in the Optical Character Reader (OCR). Generally, threshold segmentation and matching are separated. One of some methods such as iterative method, ENT, OSTU and so on is applied to threshold segmentation. But in practice, these methods are adaptive to a restricted condition. When character is distorted by random...

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...

Having accurate left ventricle (LV) segmentations across a cardiac cycle provides useful quantitative (e.g. ejection fraction) and qualitative information for diagnosis of certain heart conditions. Existing LV segmentation techniques are founded mostly upon algorithms for segmenting static images. In order to exploit the dynamic structure of the heart in a principled manner, we approach the pro...

Segmentation of handwritten input into individual characters is a crucial step in many connected handwriting recognition systems. This paper describes a segmentation algorithm for letters in Roman alphabets, curved pre-stroke cut (CPSC) segmentation. The CPSC algorithm evaluates large set of curved cuts through the image of the input string using dynamic programming and selects a small “optimal...

Speech segmentation is an important sub problem of automatic speech recognition. This research is concerned with the development of a continuous speech segmentation system using Bangla Language. This paper presents a dynamic thresholding algorithm to segment the continuous Bngla speech sentences into words/sub-words. The research uses Otsu’s method for dynamic thresholding and introduces a new ...

background: accurate brain tissue segmentation from magnetic resonance (mr) images is an important step in analysis of cerebral images. there are software packages which are used for brain segmentation. these packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. thus, assessment of the quality of the segmented gray matter (gm), ...

Image segmentation is an old and difficult problem. One of the fundamental weaknesses of current computer vision systems to be used in practical applications is their inability to adapt the segmentation process as real-world changes occur in the image. We present the first closed loop image segmentation system which incorporates a genetic algorithm to adapt the segmentation process to changes i...