Recognition of Overlapped 2D Geometrical Objects

In this paper the main focus is to study the techniques to detect or recognize the geometrical objects which are overlapped or merged with each other and to find out the best possible way to determine their respective shapes. Object detection is the process or technique of finding occurrence of real-world objects such as faces, objects, bicycles, and buildings in images or videos. Algorithms used for object detection typically use extracted features and learning algorithms to detect instances of an object division. It is commonly used in different applications such as image retrieval, security and automated vehicle parking systems. In meantime there are various different techniques available to detect object of a particular geometric shape from 2D images. But they are not much reliable techniques that identify features of objects of an image and recognize the object having geometric shape like circle, square, rectangle and triangle and other shapes. Object detection plays an important role in image processing, It helps in to identify any particular object .Object detection is basically used to identify an individual object from number of objects in an image. The proposed system includes a new algorithm to separate the touching and overlapping circles edges based on the radius range. Initial attempt include finding circles by increasing detection sensitivity and final step, include finding the dark and bright circle edges by lowering the values of edge threshold

Feature Vector Construction of 2D Images using Local and Global Features

Object recognition is a process of understanding, design, development and creation of methods to recognize the objects in the image. In this paper the main focus is to create feature vector of 2D images using local and global features of images. Feature extraction is a complex phase in image processing and computer visualization. In proposed method, color image is used as an input image. It transformed into gray-scale image. For feature vector information, local and global features are extracted. Local features are extracted using SIFT method in which key points are identified. Global features are extracted based on the intensity values of images. After that create feature vector using local and global features is high-dimensional. The proposed method is experimented using MATLAB R2012b

Dynamic bandwidth allocation with optimal wavelength switching in TWDM-PONs

Time and wavelength division multiplexed passive optical networks (TWDM-PONs) have been widely considered as one of the next evolutionary steps of optical access networks. A variety of algorithms exists that explore the problem of scheduling and wavelength assignment in TWDM-PONs. These algorithms, however, allow unlimited switching of wavelengths. In reality, wavelength switching increases guard bands due to the tuning and the switching time of components, limiting channel utilization and increasing packet delays. We propose a novel dynamic bandwidth allocation (DBA) algorithm for TWDM-PON that minimizes the performance degradation due to excessive wavelength switching

Trade-off between end-to-end reliable and cost-effective TDMA/WDM passive optical networks

Hybrid TDMA/VVDM (TWDM) Passive Optical Network (PON) is a promising candidate for Next-Generation PON (NG-PON) solutions. We propose end-to end reliable architectures for business users and a cost-effective network for residential users. We evaluate the proposed reliable architectures in terms of protection coverage, connection availability, impact of failure (i.e. to avoid a huge number of end users being affected by any single failure) and cost in different populated scenarios

Energy efficient DBA algorithms for TWDM-PONs

Energy efficiency is of a vital significance in the design of next generation time and wavelength division multiplexed passive optical networks (TWDM-PONs). In this paper, we first review strategies to save energy in TWDM-PONs using the state-of-the-art dynamic bandwidth allocation (DBA) algorithms. The DBA algorithms should not only minimize energy consumption but should impose a minimal penalty on delay performance. In this context, mainly two DBA design paradigms can be exploited: offline and online. After reviewing the performance of various design paradigms, we propose an optimal algorithm, which minimizes the energy consumption at both the OLT and the ONUs, by combining the energy efficiency due to sleep modes and the load dependent use of transceivers at the OLT. Due to this, the average energy consumption is reduced to 31%

Wavelength switched hybrid TDMA/WDM (TWDM) PON: a flexible next-generation optical access solution

In this paper, we propose the system concepts of a next-generation wavelength switched hybrid time division multiple access and wavelength division multiplexing (TWDM) passive optical network (PON) architecture. In this architecture, wavelength selective switches (WSSs) are used at the remote node to improve flexibility, data security and power budget compared to other TWDM-PON variants. We map the proposed architecture to the requirements of next-generation optical access networks in a 2020 perspective. Finally, we benchmark the proposed architecture with other proposed TWDM-PON solutions