Introduction: Virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. The segmentation of airways from CT images is a critical step for numerous virtual bronchoscopy applications. Materials and Methods: To overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy C-mean (FC-FCM), utilized...

Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without tex...

The restauration and preservation of ancient documents is becoming an interesting application in document image analysis. This paper introduces a top-down approach aimed at segmenting the graphical part in historical heritage called lettrine. The research principle was established on the concept of human visual perception and invariant texture analysis (co-occurrence and run-length matrices, au...

Everyday activities break down into parts and subparts, and appreciating this hierarchical structure is an important component of understanding. In two experiments we found age differences in the ability to perceive hierarchical structure in continuous activity. In both experiments, younger and older adults segmented movies of everyday activities into large and small meaningful events. Older ad...

Automatic segmentation of images, means being able to automatically divide an image into parts that can be analysed to give meaning. In segmentation of faces, the goal is to locate the features of the face that describes it shape. These are features like mouth, nose, eyes, eyebrows and jawline. This report describes the implementation and the theory behind a tool that does face segmentation usi...

Recent microscopic imaging systems such as whole slide scanners provide very large (up to 18GB) high resolution images. Such amounts of memory raise major issues that prevent usual image representation models from being used. Moreover, using such high resolution images, global image features, such as tissues, do not clearly appear at full resolution. Such images contain thus different hierarchi...

This paper presents an application of a hierarchical social (HS) metaheuristic to region-based segmentation. The original image is modelled as a simplified image graph, which is successively partitioned into two regions, corresponding to the most significant components of the actual image, until a termination condition is met. The graph-partitioning task is solved as a variant of the min-cut pr...

10 In this work, several thresholding and classification-based techniques were employed 11 for pixel-wise segmentation of surface defects of ‘Jonagold’ apples. Observations 12 showed that segmentation by supervised classifiers was more accurate than the 13 rest. Also, average of class-specific recognition errors was more reliable than error 14 measures based on defect size or global recognition...

A novel statistical model based on texture and shape for fully automatic intraretinal layer segmentation of normal retinal tomograms obtained by a commercial 800nm optical coherence tomography (OCT) system is developed. While existing algorithms often fail dramatically due to strong speckle noise, non-optimal imaging conditions, shadows and other artefacts, the novel algorithm's accuracy only s...

Accurate semantic labeling of image pixels is difficult because intra-class variability is often greater than inter-class variability. In turn, fast semantic segmentation is hard because accurate models are usually too complicated to also run quickly at test-time. Our experience with building and running semantic segmentation systems has also shown a reasonably obvious bottleneck on model compl...