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Hidden Markov Models (HMM) are used in handwritten strokes recognition task. The two design parameters of HMM are the number of states and number of mixtures in each state. There are two approaches for finding the number of states, namely, equal number of states and variable number of states. Since the shape of strokes will be different, variable number of states approach should be beneficial. This...
recent studies have shown a huge and steady increase in elderly population, which eventually becomes a predominant aspect of our society. As such, effective solutions that is not costly for this aspect is needed. Recently, a lot of work has been conducted on Ambient Assisted Living (AAL) which focuses on elderly peoples need. Ambient Intelligence technologies are widely researched on and developed,...
Face recognition is an important technique for Natural User Interface (NUI) and Human Robot Interaction (HRI) and many of the current state-of-the-art face recognition techniques are based on the local features which are extracted from a face alignment method like Constrained Local Model (CLM). But, in a real world environment, face alignment methods often fail to correctly localize the features because...
Most of the approaches for indoor RGBD semantic labeling focus on using pixels or super pixels to train a classifier. In this paper, we implement a higher level segmentation using a hierarchy of super pixels to obtain a better segmentation for training our classifier. By focusing on meaningful segments that conform more directly to objects, regardless of size, we train a random forest of decision...
Achieving sub-pixel accuracy with face alignment algorithms is a difficult task given the diversity of appearance in real world facial profiles. To capture variations in perspective, occlusion, and illumination with adequate precision, current face alignment approaches rely on detecting facial landmarks and iteratively adjusting deformable models that encode prior knowledge of facial structure. However,...
PASCAL VOC Segmentation Challenge [10] is currently considered as one of the datasets that reflect the image segmentation difficulties for real world scenarios [29]. However, current evaluation is simply based on a single Inter-section Over Union (IOU) score. In this paper, we try to discover the error factors under the IOU, which makes the results more informative to understand rather than a black...
Motion trajectory analysis is important for human motion recognition and human computer interaction. In this paper, we propose a flexible 3D trajectory indexing method for complex 3D motion recognition. Based on both point level and primitive-level descriptors, trajectories are represented in the sub-primitive level, the level between the point level and primitive level. Primitives are flexibly segmented...
This paper presents an automated method for counting red blood cells present in a blood sample. The proposed method addresses the problems of holes present in blood cells and overlapping characteristics of the red blood cells. The procedure is quite simple and straightforward, which utilizes mathematical morphological operations of erosion and dilation for performing different steps. It first thresholds...
Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (Conv Net) features. We introduce a range of condition variations to explore the robustness of these features, including: translation,...
EEG based upper limb rehabilitation has limitation on the control commands of neuro-prosthetics cannot deal with human's real movements. To resolve this problem, it is important to know about neural correlation of the directions of arm movement. Previous studies classified the directions of arm movement, using center-out task, only including y-z-axis movement. In this research, 4 subjects participated...
Many plants are facing the risk of extinction due to unplanned urbanization and over growth of population. Digital databases of plants should be maintained for proper tracking of local flora and making data-driven policies/decisions for their preservation. Plant identification is important for medical as well as educational purposes but maintaining an exhaustive digital database is a challenging task...
A method is presented for authenticating people on the basis of lip movement. It uses the kernel mutual subspace (KMS) method using fusion of canonical angles by kernel Fisher discriminant analysis. Its authentication accuracy is better than that of previously proposed lip-movement authentication methods when the distribution of lip images has a nonlinear structure. The similarity of KMS is canonical...
Whole brain tractography generates a very huge dataset composed by various tracts of different shapes, lengths, positions. Then clustering them into anatomically meaningful bundles is a challenge. Until now, several clustering methods have been proposed such as methods based on similarity measures or methods based on anatomical information, but no optimal clustering criteria were found yet. All methods...
Content based image retrieval has become a major research interest recently. This paper presents an improved image similarity measure for image retrieval system. In the region based image comparison, two images are usually compared in terms of sum of the Euclidean distances among their regions. In this work, the image similarity measure is enhanced through a fuzzyfication of regions' importance and...
In the recent years, contour-based shape representation is an important issue in the object recognition research area. In this paper, a new shape descriptor A-DCE is proposed based on DCE and DP for contour deformation and recognition. Firstly, the object contour is evolved adaptively by DCE to extract the contour information with important visual parts. Secondly, the costing feature descriptor is...
The aim of this paper is to develop an effective classification approach based on Random Forest (RF) algorithm. Three fruits; i.e., apples, Strawberry, and oranges were analysed and several features were extracted based on the fruits' shape, colour characteristics as well as Scale Invariant Feature Transform (SIFT). A preprocessing stages using image processing to prepare the fruit images dataset...
In real-time anomaly detection problems, reducing the dimensionality and improving recognition rate are two most crucial problems. The unbalanced data distribution is one of main reasons of leading to low recognition rate. In this paper, a hybrid approach using Tabu search (TS) and ensemble classification algorithm is proposed. Tabu search is simultaneously applied to select features and weights of...
This paper presents the detection and localization methods of entrance and staircase markers for the team E-Mobile in TechX Challenge 2013. Autonomous vehicles are required to detect and locate traffic cones beside the indoor entrance and staircase. One big challenge is from the unpredictable lighting conditions and environment. Different practical techniques such as color space selection, segmentation,...
This research is to propose a fast and highly accurate object recognition method especially for fruit recognition applications to be used in a mobile environment. Conventional techniques are based on one or more of the basic features that characterize an object: color, shape, texture and intensity, causing performance or accuracy limitations in a mobile environment. Thus, this paper presents a combined...
Currency recognition system is one of the fast growing research fields under image processing. This paper proposes a novel method for Indian currency recognition. Our proposed approach identifies denomination by extracting features like Center Numeral, Shape, RBI Seal, Latent Image and Micro Letter. Principal Component Analysis is used to reduce the dimensions and a similarity based classifier is...
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