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This paper presents a novel image classification method based on integration of EEG and visual features. In the proposed method, we obtain classification results by separately using EEG and visual features. Furthermore, we merge the above classification results based on a kernelized version of Supervised learning from multiple experts and obtain the final classification result. In order to generate...
Accurate and automatic detection and delineation of cervical cells are two critical precursor steps to automatic Pap smear image analysis and detecting pre-cancerous changes in the uterine cervix. To overcome noise and cell occlusion, many segmentation methods resort to incorporating shape priors, mostly enforcing elliptical shapes (e.g. [1]). However, elliptical shapes do not accurately model cervical...
Cell migration is a fundamental process for the development and maintenance of all multicellular organisms. Accurate cell tracking may lead to better interpretations of long-term cell behaviours. This paper describes an automated system to track multiple cells from experimental phase contrast images, which includes image registration, lumen segmentation, cell candidate detection, and multiple hypothesis...
Interactive mobile vision applications, such as Mobile Landmark Recognition (MLR), have recently attracted ever increasing research attention due to the exponential growth of mobile devices. However, the recognition accuracy retains as a bottleneck hesitating the proliferation of such applications. To address this challenge, in this paper we design a novel framework based on interactive image segmentation...
Image segmentation method combined with Markov random field (MRF) model and regional growth image in this paper is proposed to achieve the accuracy of sonar image segmentation. First of all, the characteristics of field and the label field of sonar image is established through the MRF model; secondly, the further image segmentation is processed by region growing based on the initial image segmentation...
The coronary cine-angiogram (CCA) is an invasive medical image modality which is used to determine the luminal obstructions or stenosis in the Coronary Arteries (CA). CCA based quantitative assessment of vascular morphology is a demanding area in medical diagnosis and segmentation of blood vessels in CCAs is one of the mandatory step in this endeavor. The accurate segmentation of CAs in Angiogram...
Though blood cell manipulation has been an interesting research area for many years, most of the techniques presented in literature produce poor segmentation results for images with high overlapped blood cells. In this paper, we introduce a fully automatic low cost and accurate system to identify four common types of anemia and report on blood cell count. The results of our system indicate a good...
Nuclear segmentation is one of the challenging issues in the field of Medical Image segmentation for Histopathological Images. Various edge based and region based approaches have been proposed in the literature. Both the approaches suffer from deficiencies such as poor edge information and over/under segmentation respectively. In the recent past, Active contours have emerged as a powerful techniques...
In forensic face comparison, one of the features taken into account are the eyebrows. In this paper, we investigate human performance on an eyebrow verification task. This task is executed twice by participants: a "best-effort" approach and an approach using features based on forensic knowledge. The group of participants is divided into forensic/biometric experts and non-experts. The rationale...
This paper proposes a simple approach to split the clumps found in Histopathological Images. Watershed algorithm is generally used to segment and separate the clumps. Several studies have revealed that watershed algorithm suffer drawbacks leading to lesser accuracy in clump splitting. From the literature it is evident that most of the existing methods on clump splitting have been applied on binary...
This work proposes a new segmentation algorithm for three-dimensional dense point clouds and has been specially designed for natural environments where the ground is unstructured and may include big slopes, non-flat areas and isolated areas. This technique is based on a Geometric-Featured Voxel map (GFV) where the scene is discretized in constant size cubes or voxels which are classified in flat surface,...
In this work we address the problem of semantic segmentation of urban remote sensing images into land cover maps. We propose to tackle this task by learning the geographic context of classes and use it to favor or discourage certain spatial configuration of label assignments. For this reason, we learn from training data two spatial priors enforcing different key aspects of the geographical space:...
In this study, the unsupervised detection of urban changes, based on high-spatial resolution SAR imagery, is approached using the object-oriented paradigm. Multidate images segmentation strategy was adopted to avoid the creation of sliver polygon. Following segmentation, a change image was generated by comparing objects' mean intensities using a modified version of the traditional ratio operator....
This paper introduces an screening method for detecting glaucoma using rim width indicator. Due to some special cases, such as myopia eye, only cup-to-disc ratio may not efficient for screening glaucoma. Rim width based on ISNT rule can be a feature for classification. Rim width in each section of optic nerve will be measured and then we compare them with ISNT rule for glaucoma classification. According...
The detection and analysis of retinal vessels in ophthalmology is of great use in the diagnosis and progression monitoring of diabetic retinopathy. Automatic Detection of the vessel network has however been challenging due to noise from uneven contrast and illumination during the retinal image acquisition process. This paper presents a robust segmentation technique that combines phase congruence and...
The rapid expansion of human activities in time and space is tangible in different parts of the world. Urban sprawl is one of the phenomena that need to be controlled in order to ensure a sustainable development of communities. Satellite remote sensing provides a repository of Earth observations - and thus information on surface changes - since the early seventies. This research proposes a hybrid...
Biometric is a method to identify human using the specific feature based on part of human body. Nowadays, biometric is widely used because of the performance to identify human. The palm-print data-set used in this research were manually collected that consist of 110 people with 10 images for each person. Palm-print recognition system consist of : region of interest (ROI) extraction using Competitive...
The prediction of individual characteristics from biometric data which falls short of full identity prediction is nevertheless a valuable capability in many practical applications. This paper considers age prediction in two biometric modalities (iris and handwritten signature) and explores how different feature types and classification strategies can be used to overcome possible constraints in different...
Different clustering based strategies have been proposed to increase the performance of image segmentation. However, due to complexity of chip preparing process, the real microarray image will contain artifacts, noises, and spots with different shapes, which result in these segmentation algorithms can't meet the satisfactory results. To overcome those drawbacks, this paper proposed an improved k-means...
Development of Optical Character Recognition (OCR) for printed Roman script is still an active area of research. Automatic Style Identification (ASI) can be used to improve the performance of OCR system and keyword spotting techniques for printed Roman script. This paper proposes a two stage font invariant technique for detection of italic, bold, underlined, normal and all capital styled words for...
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