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Detection, and localization of Bangla text from natural scene images are important prerequisites for developing Bangla OCR as well as many content-based image analyses. But there is no standard Bangla OCR to be used in the daily work. Due to the presence of some unique features, detection and localization of Bangla text have become more challenging than English text. In this paper, we have proposed...
Iris recognition is a biometric authentication system proving vital for ensuring security and has been employed as an important case to test the algorithms developed in pattern recognition. The unique circular shape of the iris and its time invariance makes it a versatile technique that has an accuracy that can be mathematically proven. Here in this work we propose a new segmentation technique and...
Individuality of handwriting is the reason why it is used as a common base element for detecting character traits of the writer. It is believed that dynamic information improve the accuracy of the analysis, but they are not contained in an offline handwritten text. In order to recover dynamic information, a novel approach for handwriting trajectory recovery is proposed in this paper. The procedure...
This research aims to examine the effectiveness and efficiency of fuzzing hashing algorithm in the identification of similarities in Malware Analysis. More precisely, it will present the benefit of using fuzzy hashing algorithms, such as ssdeep, sdhash, mvHash and mrsh – v2, in identifying similarities in Malware domain. The obtained results will be compared with the traditional and most common Cryptographic...
Movement primitive segmentation enables long sequences of human movement observation data to be segmented into smaller components, termed movement primitives, to facilitate movement identification, modeling, and learning. It has been applied to exercise monitoring, gesture recognition, human–machine interaction, and robot imitation learning. This paper proposes a segmentation framework to categorize...
In this paper, Face recognition system using improved artificial bee colony algorithm is proposed. This system works on two different phases, named as Extraction phase and Recognition phase. In the extraction phase, sub-window extraction algorithm is applied on different face images collected from different sources. Then applied artificial bee colony algorithm to reduce number of sub windows, taken...
Extensive research has been conducted in an effort to evaluate methods and techniques for image segmentation. However, while most literature has focused on evaluating automatic and semi-automatic algorithms, works evaluating interactive segmentation algorithms are less numerous. Note that interactive segmentation can improve results by adding prior knowledge from users into the process. Although this...
The aim of this study is the detection and segmentation of microcalcifications in digital mammograms using multifractal analysis. To detect the suspicious Region Of Interest (ROI), containing anomalies, we propose to decompose the whole image into ROIs and compare the multifractal spectrums based on the q-structure functions of each one. The segmentation of microcalcifications consists of two steps...
Efficiency and effectiveness are two key factors to evaluate a human segmentation algorithm for real vision applications. However, most existing algorithms only focus on one of them. That is, fast and accurate human segmentation is not yet well addressed. In this paper, we propose a super-fast and highly accurate human segmentation method with very deep convolutional neural networks. We also provide...
This paper proposes a novel method via dynamic tree to solve the non-rigid registration of point sets with large shape difference which is a difficult problem for existing methods. Affine ICP algorithm with bidirectional distance is employed to evaluate the similarity between two point sets, and then non-rigid registration is conducted on similar models and subjects. Subjects with accurate registration...
Image processing-based analysis of microscopic leukocyte helps in early detection of many diseases. It is a challenging issue to segment leukocytes under uneven imaging conditions since features of microscopic leukocyte images change in different labratories. This paper introduces an automatic robust method to segment leukocyte from blood microscopic images using intuitionistic fuzzy divergence based...
A novel approach to land masking in synthetic aperture radar (SAR) images is designed and implemented. The developed algorithm takes as input an archived shoreline from a public domain database and modifies it to draw the actual shoreline on SAR images by analysing backscatter values. Starting with data from the GSHHS (the global self-consistent hierarchical high-resolution shoreline database), coastline...
Activated sludge process form an important part of wastewater treatment plant with domestic effluent. The variations in the state of the process are appeared as those in the size and structure of flocs and filaments found in the wastewater samples from aeration tank of secondary treatment. The normal operation requires proper settling of flocs in the secondary clarifier, which is affected by problem...
Computer based modeling and analysis of blood vessel (BV) networks is essential for automated detection and tracking of anomalies and structural changes in retina images. Among many published techniques for automated BV mapping, optimal selection of thresholds to delineate BV pixels from their background pixels remains an open problem. In this paper we propose a novel representation of a BV pixel...
This paper proposes a clustering based image segmentation approach for elephant recognition. Appreciable recognition rate was achieved by k-means clustering technique followed by feature extraction and K nearest neighbour (K-NN) classifier. The k-means algorithm employs the concept of fitness and belongingness to provide a more adaptive andbetterclustering process as compared to several conventional...
An effective graph-based image segmentation using superpixel-based graph representation is introduced. The techniques of SLIC superpixels, 5-D spectral clustering, and boundary-focused region merging are adopted in the proposed algorithm. With SLIC superpixels, the original image segmentation problem is transformed into the superpixel labeling problem. It makes the proposed algorithm more efficient...
The objective of segmentation operation is to separate the mass from the rest of the breast by trying to delimit its borders correctly. This article presents a semi-automatic mass extraction method by application of an adaptive region growing segmentation technique. The region growing process is guided by regional feature analysis; consequently, the result will be a robust algorithm able of respecting...
This paper deals with research in the area of image analysis. Our approach is based on hybrid segmentation and Scale-Invariant Feature Transform (SIFT) method. The main idea is to improve the process of object recognition and their classification into classes by Support Vector Machine (SVM) classifier. The fast and powerful hybrid segmentation algorithm based on Mean Shift and Believe Propagation...
We solve the problem of localizing and tracking household objects using a depth-camera sensor network. We design and implement Kin sight that tracks household objects indirectly -- by tracking human figures, and detecting and recognizing objects from human-object interactions. We devise two novel algorithms: (1) Depth Sweep -- that uses depth information to efficiently extract objects from an image,...
Iris recognition has been used mainly to recognize cooperative subjects in controlled environments. With the continuing improvements in iris matching performance and reduction in the cost of iris scanners, the technology will witness broader applications and may be confronted with newer challenges. In this research, we have investigated one such challenge, namely matching iris images captured before...
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