Current Issue : October - December Volume : 2013 Issue Number : 4 Articles : 5 Articles
Face landmarking, defined as the detection and localization of certain characteristic points on the face, is an important\r\nintermediary step for many subsequent face processing operations that range from biometric recognition to the\r\nunderstanding of mental states. Despite its conceptual simplicity, this computer vision problem has proven extremely\r\nchallenging due to inherent face variability as well as the multitude of confounding factors such as pose, expression,\r\nillumination and occlusions. The purpose of this survey is to give an overview of landmarking algorithms and their\r\nprogress over the last decade, categorize them and show comparative performance statistics of the state of the art.\r\nWe discuss the main trends and indicate current shortcomings with the expectation that this survey will provide\r\nfurther impetus for the much needed high-performance, real-life face landmarking operating at video rates....
Diabetic Retinopathy - a complication of diabetes mellitus - is a severe and wide-spread eye disease: it is the leading cause of legal blindness for the working age population in western countries. For the diagnosis of Diabetic Retinopathy, digital color fundus images are becoming increasingly important. This fact opens the possibility of applying image processing techniques in order to facilitate and improve diagnosis in different ways. Since microaneurysms are earliest sign of DR, therefore an algorithm able to automatically detect the microaneurysms in fundus image captured is a necessary preprocessing step for a correct diagnosis. This paper aims to develop and test a new method for detecting the microaneurysms in retina images. To do so preprocessing, gray level 2D feature based vessel extraction is done using neural network. The method is evaluated on DRIVE database and average accuracy of 0.9361 is obtained which is superior than other rule based methods in literature. To identify microaneurysms in an image morphological opening and image enhancement operations are performed. A MATLAB implementation of the complete algorithm is developed and tests suggest that the diagnosis in an image can be estimated in shorter time than previous techniques with the same or better accuracy....
The most effective method for detection of early breast cancer is mammography, which is the most reliable method for the detection of early breast cancer, Mammography is the compulsory and only option for the premature detection of breast cancer in women, of all diagnostic methods currently available for this purpose this is more reliable method.This paper present a wavelet and window method to detect breast tumours using wavelet thresholding. The compressed image is decomposed at level 4 using daubechies 6 wavelet and histograms for all components (approximation, horizontal, vertical & diagonal) is evaluated for first two level and only approximation components are calculated for remaining two level. Further the histogram of horizontal, vertical and diagonal components are decomposed at level 5 and the thresholds corresponding to minima of the histogram is found. Transferring those thresholds at components horizontal, vertical and diagonal are thresholded. Further a global threshold is found to segment reconstructed image, fine segmentation is done using window based operation & using a wavelet approach for final threshold. Depending upon the threshold values, the suspicious areas have been segmented. The works effection in an over segmented image. The related work was implemented using image processing tools, and using the MATLAB....
This paper presents a phenomenon for extraction of the vehicle number plates from the vehicle images using convolution morphology techniques. The main concept is to use different morphological operations in such a way so that the number plate of the vehicle can be perfectly recognized. The phenomenon makes the task of extraction and recognition of the number plate independent of different parameter like color, size and location of number plate. The proposed approach involves different processes, enhance image, morphing transformation, getting possible candidates for resultant images and extracting the number plate from these possible candidates. This algorithm can correctly detect the number plate area from the vehicle image....
This paper presents a camera-based lane departure warning system implemented on a field programmable gate array\r\n(FPGA) device. The system is used as a driver assistance system, which effectively prevents accidents given that it is\r\nendowed with the advantages of FPGA technology, including high performance for digital image processing\r\napplications, compactness, and low cost. The main contributions of this work are threefold. (1) An improved vanishing\r\npoint-based steerable filter is introduced and implemented on an FPGA device. Using the vanishing point to guide\r\nthe orientation at each pixel, this algorithm works well in complex environments. (2) An improved vanishing\r\npoint-based parallel Hough transform is proposed. Unlike the traditional Hough transform, our improved version\r\nmoves the coordinate origin to the estimated vanishing point to reduce storage requirements and enhance detection\r\ncapability. (3) A prototype based on the FPGA is developed. With improvements in the vanishing point-based\r\nsteerable filter and vanishing point-based parallel Hough transform, the prototype can be used in complex weather\r\nand lighting conditions. Experiments conducted on an evaluation platform and on actual roads illustrate the effective\r\nperformance of the proposed system....
Loading....