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Facial expression is a significant key for interpersonal relations where non verbal cues are conveyed from person to person. Automated recognition of facial expression plays an important role in widely of applications such as human-computer interaction, data-driven animation, clinical practice and behavioral science. In this study a novel and efficient automated recognition of facial expression system...
The leading cause of cancer mortality among women arises due to breast cancer. Digital mammogram plays an important role for cancer diagnosis. The early sign of breast cancer is the appearance of microcalcifications clusters on mammogram images. An efficient method to classify the microcalcification severity is presented in this paper. Tetrolet transform also named as adaptive Haar transform is utilized...
By applying an edge detection algorithm the silhouettes of objects can be efficiently detected in an image or tracked through multiple frames. Traditional methods of object detection ignore information about an object being tracked. This information can be used to reduce processing time and increase accuracy of object detection. This paper proposes a method that uses this information to provide a...
In this work, we present a novel method for accurate affine transformation estimation of image regions. We illustrate the benefits of using such a method in a point matching mechanism that enables locating large amount of point matches with high geometric precision and low rate of false matches. Recent publications have shown that considering the affine transformation model of local regions, is extremely...
To improve phase offset estimation accuracy without estimating signal's centre frequency, a cross correlation method based on Hilbert transform was proposed. Firstly, we described the principle of Hilbert transform method and correlation method respectively. Then, we proposed a cross correlation method based on Hilbert transform to calculate phase offset. Finally, comparative experiments were implemented...
Identification of power quality events is one of key tasks in power system protection. This paper presents a new approach based on compressive sensing (CS) for classifying multiple power quality disturbances (PQD). First, every test event sample of PQD is represented as a sparse linear combination of training event samples using sparse representation. A lower-dimensional random matrix is then applied...
The online recalibration of multi-sensor systems is a fundamental problem that must be solved before complex automated systems are deployed in situations such as automated driving. In such situations, accurate knowledge of calibration parameters is critical for the safe operation of automated systems. However, most existing calibration methods for multisensor systems are computationally expensive,...
There is growing interest among smartphone users in the ability to determine their precise location in their environment for a variety of applications related to way finding, travel and shopping. While GPS provides valuable self-localization estimates, its accuracy is limited to approximately 10 meters in most urban locations. This paper focuses on the self-localization needs of blind or visually...
In this paper a proposed method for gesture recognition using depth map image is presented. Three different feature extraction methods are presented too. All of them are based on Radon transform. First method reduces the feature vector of Radon transform by averaging its values. Next approach uses discrete cosine transform on radon graph, thus the energy of graph is reorganized. This approach concentrates...
In this paper, we present the encoding produces technique for texture recognition. This produces are developed with the purpose to replaced the previous method. Firstly, we encode image informations by VTT (Volume Trace Transform), and trace functionals are chosen by RL (Reinforce Learning). The number of VTT results are extracted by the amount of trace functionals. Secondly, we present P-DFT (Plus-Discriminant...
Industrial environments are rarely static and often their configuration is continuously changing due to the material transfer flow. This is a major challenge for infrastructure free localization systems. In this paper we address this challenge by introducing a localization approach that uses a dual-timescale approach. The proposed approach — Dual-Timescale Normal Distributions Transform Monte Carlo...
The constrained two-bit transform (C2BT) is recently proposed for low complexity motion estimation (ME) to reduce the high computational complexity of the typical two-bit transform (2BT) while maintaining the ME accuracy. And the bit-inverted Gray-coded bit-plane matching (BGCBPM) is also proposed to enhance the ME accuracy. In this paper, we propose a fast ME algorithm exploiting these two bit-plane...
The presence of both graphics and scene text in video frames makes text detection and recognition problem more challenging because the nature of the two texts differs significantly. This paper aims to propose a novel method for separation of graphics and scene text to achieve good recognition rate based on the fact that Canny and Sobel edge pattern share common property for text. We propose to use...
This work presents a binarization technique of map document images. It exploits an amalgam of global and local threshold approaches best suited for binarization of document images with complex background and overlapping objects in the foreground like maps. The proposed approach uses Distance Transform (DT) and Adaptive threshold. Initially a rough estimate of the map background is done using Distance...
An automatic building extraction method for very high resolution satellite images is presented in this paper. Two novel operators Differential Morphological Shadow Operator (DMSO) and Differential Morphological Building Operator (DMBO) for extracting shadows and buildings respectively are proposed. The method identifies shadows using DMSO. After masking out the shadow, DMBO is applied to obtain the...
This paper presents a two layer texture modeling method to recognize architectural distortion in mammograms. We propose a method that models a Gaussian mixture on the Curvelet coefficients and the outputs of Spiculated Lesion Filters. The Curvelet transform and the Spiculated Lesion Filters have been applied to extract textural features of mammograms in literature. However the key difference between...
Brain-computer interfaces (BCIs) aim to provide a non-muscular channel to communicate with the external world through the use of the brain Electroencephalograph (EEG) activity. A crucial step in such an operation is brain signal processing methods. BCI systems use EEG as it is practical, noninvasive, cheap and has real time capability imaging technology. BCI's efficiency is dependent on brain signal...
Image registration is one of the crucial steps in the analysis of remotely sensed data. A new acquired image must be transformed, using image registration techniques, to match the orientation and scale of the related reference images. Image registration requires intensive computational effort not only because of its computational complexity, but also due to the continuous increase in image resolution...
Real-time road lane recognition and position estimation algorithm in small vehicle is generally limited by the amount of processing power available. The goal of this research is to develop a light-weight algorithm to recognize a pair of road lane markers using computer vision and to estimate the vehicle position relative to the lane markers. The road lane recognition algorithm uses inverse perspective...
Septic shock is a leading cause of hospital deaths in the United States. A system to detect initial immune response to an infection could allow for treatment before septic shock occurs, which would save many lives. Here, we demonstrate the analysis of beat-to-beat heart rate intervals using the Hilbert-Huang transform (HHT) as a method of detection of the immune/inflammatory response. The HHT is ideal...
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