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Nowadays, it is hard to distinguish the type of orchid leaf diseases just by using naked eyes. This paper presents an image segmentation technique for classify two difference types of orchid leaf disease such as black leaf spot and sun scorch. The orchid leaves images were digitally captured by using digital camera. With respect to the region of interest selected orchid leaves are analyze by using...
Depth information can be obtained using stereo matching algorithms, which compute the horizontal displacement (disparity) of the corresponding points and convert to depth information using the triangular relation. However, the matching process is challenging with presence of textureless regions. This paper proposes a novel disparity refinement method for stereo matching based on Semi-global Matching...
In this paper we propose a new high-quality and efficient single image super-resolution model that extends exploit the self-similarity property. The similarity of frequency error compensation between the high-resolution patch and low-resolution model can modeled as a optimization problem. Based on the in-place patch similarity, the optimization model is further simplified to alleviate the computing...
Moving object detection used in wide range of application especially in automated traffic surveillance and management. In defense, these techniques are used in automating threat detection and elimination, target acquisition and also in underwater object tracking. Moving object detection is carried using various methods and an analysis is made to know its precision of detection. The methods on which...
In this paper, a co-segmentation method to extract the cortex in inter-subject brain MR (Magnetic Resonance) images is proposed. Co-segmentation is a method to segment two images simultaneously. The method employs the MRF (Markov Random Field) based graph for contstructing the objective function and the graph-cut algorithm for opimization. In the graph construction, similarity nodes are added to represent...
We propose edge-preserving regularization for color image demosaicing in the realistic case of noisy data. We enforce both intrachannel local smoothness of the intensity, and interchannel local similarities of the edges. To describe these local correlations while preserving even the finest image details, we exploit suitable functions of the derivatives of first, second and third order. The solution...
To achieve an online robotic path planning system which can dynamically react to environmental changes, the study proposes a real-time system which updates locally the input information and re-plans in time an alternative path for consecutive following under restrained computing capability of the agent. The system consists of a framework of functions to switch the working space successively into so-called...
Recent advances in text detection allow for finnding text regions in natural scenes rather accurately. Global features in content based image retrieval, however, typically do not cover such a high level information. While characteristics of text regions may be reflected by texture or color properties, the respective pixels are not treated in a different way. In this contribution we investigate the...
In this paper, we process the image of Chinese characters, and assess the regular of Chinese characters in the image. Images of Chinese handwritten characters is processed to remove the irrelevant information such as background color, background noise. After processing and Hough transforming the image, we can get the information of strokes and angle through the outline of the image. After Hough transforming,...
Modularity is widely used to effectively measure the strength of the disjoint community structure found by community detection algorithms. Although several overlapping extensions of modularity were proposed to measure the quality of overlapping community structure, there is lack of systematic comparison of different extensions. To fill this gap, we overview overlapping extensions of modularity to...
In this paper we investigate two real crime-related networks, which are both bipartite. The bipartite networks are: a spatial network where crimes of various types are committed in different local government areas; and a dark terrorist network where individuals attend events or have common affiliations. In each case we analyse the communities found by a random-walk based algorithm in the primary weighted...
Most of overlapping community detection algorithms cannot be applied to networks with highly overlapping community such as online social networks where individuals belong to many communities. One important reason is that many algorithms detect communities based on the explicit borders where nodes have more connections inside the communities, however, when the vertices' membership number gets large,...
Community detection is one of the most important problems in social network analysis in the context of the structure of the underlying graphs. Many researchers have proposed their own methods for discovering dense regions in social networks. Such methods are only designed with links of the underlying social network. However, with the development of recent applications, rich edge content can be available...
We present our novel community mining algorithm that uses only local information to accurately identify communities, outliers, and hubs in social networks. The main component of our algorithm is the T metric, which evaluates the relative quality of a community by considering the number of internal and external triads (3-node cliques) it contains. Furthermore we propose an intuitive statistical method...
Most real-world social networks are inherently dynamic and composed of communities that are constantly changing in membership. As a result, recent years have witnessed increased attention toward the challenging problem of detecting evolving communities. This paper presents a game-theoretic approach for community detection in dynamic social networks in which each node is treated as a rational agent...
In this paper, a super-resolution technique is proposed that uses a combination of bicubic interpolation and wavelet transform. Bicubic interpolation produces a high resolution image but is prone to blurring artifact. So the blurring artifact is reduced in the wavelet domain. The input low-resolution is up-sampled using bicubic interpolation. The edges of the resultant high-resolution image are enhanced...
License plate recognition (LPR) plays a major role in this busy world, as the number of vehicles increases day by day, theft of vehicles, breaking traffic rules, entering restricted area are also increases linearly, so to block this act license plate recognition system is designed. License Plate Recognition systems basically consist of 3 main processing steps such as: Detection of number plate, Segmentation...
Indian stone inscriptions play an important role in the reconstruction of the history of India. Kannada is considered the oldest language next to Sanskrit, Prakrit, and Tamil. According to linguists Tamil and Kannada branched off simultaneously from the Dravidian language of South India before the Christian Era. Indian epigraphy becomes more widespread over the 1st millennium, engraved on the faces...
Rain and snow are two of the major obstacles in processing the photograph captured in the outdoor bad weather conditions. Rain and snow will cause the performance of vision algorithm become worse. There are a lot of methods have been proposed to reduce the raindrops and snowflakes in video. However, how to remove rain and snow and keep the detail of the background in a single image is still quite...
It is important to recognize and diagnose the various forms of ovulatory failure that can contribute to infertility. It is likely that there are many explanations for ovulation failure. One type of failure is polycystic ovary syndrome (PCOS). PCOS is an endocrine disorder, which is characterized by the formation of many follicles in the ovary. This disorder seriously affects women's health, such as...
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