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In this paper, we are mostly interested in investigating how the study and discovery of the human visual cortex could be utilised to improve the computational models for visual recognition by computer vision. Many of the brain perceptual abilities in vision have corresponding algorithms exist in computer vision, and in this paper we discuss three such models. First we present a model that has the...
This paper presents new class of time-frequency (T-F) features for automatic detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived from the instantaneous frequency and energies of EEG signals in different spectral sub-bands. The proposed features based on image descriptors are extracted from the T-F representation...
Statistical shape models generally characterize shape variations linearly by principal component analysis (PCA), which assumes that the non-rigid shape parameters are drawn from a Gaussian distribution. This practical assumption is often not valid. Instead, we propose a constrained local model based on independent component analysis (ICA) and use kernel density estimation (KDE) for non-parametrically...
Robust and accurate segmentation of blood vessels is important for treatment and diagnosis of cardiovascular diseases. Here, we introduce a new approach for 3D segmentation of vessels which is formulated as a convex parameter estimation problem and combined with an incremental tracking approach. Parameter values are determined as global optimum of a semidefinite program and admissible shape variations...
Topological signal processing, especially persistent homology, is a growing field of study for analyzing sets of data points that has been heretofore applied to unlabeled data. In this work, we consider the case of labeled data and examine the topology of the decision boundary separating different labeled classes. Specifically, we propose a novel approach to construct simplicial complexes of decision...
We present a technique for estimating the shape and reflectance of an object in terms of its surface normals and spatially-varying BRDF. We assume that multiple images of the object are obtained under fixed view-point and varying illumination, i.e, the setting of photometric stereo. Assuming that the BRDF at each pixel lies in the non-negative span of a known BRDF dictionary, we derive a per-pixel...
Lung cancer is the second most common cancer in the United States, regardless of gender. Lung cancer staging is a critical process for diagnosis and prognosis that is commonly done through the analysis of computed tomography of the chest. Analysis can be done by extracting quantitative metrics from clinician defined contours; however, defining contours manually can be a time consuming process which,...
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...
Plant leaves provide sufficient features to distinguish them among other species. Identification of plants using leaf images is a classic problem in digital image processing. Usually those image processing systems use shape based digital morphological features for leaf identification task. Even there are number of studies on leaf based plant identification, very few of them are for mobiles. In this...
The automatic recognition of planes in aerial images is an important application in the image analysis field. However, it remains a problem despite many years of work due to the arbitrary original poses and the variation in the shapes of planes. This paper proposes a novel approach for automatic aircraft detection based on statistical theory and common features of different kinds of planes. Experiments...
Character recognition techniques for printed documents are widely used for English language. However, the systems that are implemented to recognize Asian languages struggle to increase the accuracy of recognition. Among other Asian languages (such as Arabic, Tamil, Chinese), Sinhala characters are unique, mainly because they are round in shape. This unique feature makes it a challenge to extend the...
3D applications appear in every corner of life in the current technology era. There is a need for an ubiquitous 3D input device that works with many different platforms, from head-mounted displays (HMDs) to mobile touch devices, 3DTVs, and even the Cave Automatic Virtual Environments. We present 3DTouch, a novel wearable 3D input device worn on the fingertip for 3D manipulation tasks. 3DTouch is designed...
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 research reports the findings of experiments conducted in Kuwait to explore how randomness in educational engineering video games can assist autistic children in experiencing randomness and developing their cognitive behaviors. The experiments are based on an engineering educational application that was implemented based on random numbers and by using the Stroop effect theory. Different scenarios...
Preprocessing and fusion techniques for finger vein recognition are investigated. An experimental study involving a set of preprocessing approaches shows the importance of selecting the appropriate single technique and the usefulness of cascading several different preprocessing methods for subsequent feature extraction of various types. Score level fusion is able to significantly improve recognition...
Conventional equivalence principle algorithm (EPA) employs cubical boxes to support equivalence sources. However, it introduces strong discontinuities. In this work, a spherical surface is employed as the equivalence surface in EPA to avoid singularities from non-smooth surfaces. Further to achieve high order accuracy, meshless samples are used for the integrals on the spherical surface to avoid the...
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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