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Line drawing from a 1938 architectural plan drawn on linen was successfully extracted using Difference-of-Gaussian (DoG) filters. Compared to traditional edge detection and image segmentation techniques, the DoG filter was able to exclude canvas weave patterns and stain without additional morphological operations. The output image using DoG filter can be used for vectorizing the extracted architectural...
The main objective of this paper is to present an analytical method to detect lesions (cysts) in digitized MRI data. Segmentation techniques are applied on different sequences of MRI images (T1&T2) which helps to differentiate between malignant region from normal region in the given original image. The abnormal part is captured in the JPEG format. The segmentation of the image is then used to...
We propose a fast rectangle and triangle detection method applicable in the target recognition and pose estimation of spacecraft. The algorithm makes use of a new line segment detector based on orientation histogram and Bresenham's line drawing algorithm. The detected line segments are categorized into different groups according to their angles, by which we can quickly detect and locate rectangle...
This paper addresses the problem of finding edges of buildings in high-resolution remotely sensed images, which is of great help for subsequent analysis of built-up areas in urban remote sensing. More precisely, we propose a novel algorithm to extract meaningful edges associated to buildings with their saliency, by integrating an edge detection procedure with a junction process. This is inspired by...
Automated analysis of the segment LCD images may be utilized to detect hardware or software related problems of the device or LCD itself. The malfunction may be revealed through detection of faulty segments. Difficulties to automate image analysis arise from existing intensity and geometric distortions. We adopt concepts of biological visual systems to improve performance of computational system....
Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and...
‘Maximally Stable Extremal Regions’ (MSER) based interest points are frequently used for medical image registration on account of their robustness to noise, better localization, and good repeatability. However, if the objects in the image do not have sharp boundaries (as is the case with medical images), the number of MSER's detected is low. Also, MSER's are highly sensitive to image blur. This paper...
Pedestrian detection under changing environment is very challenging, especially with pedestrians approaching suddenly. This paper proposes a novel pedestrian detection algorithm using a unique combination of Discrete Cosine Transform based Haar Cascade Detector (DHCD) along with Single bounding box convergence using Skin color segmentation, to detect a single pedestrian. Discrete Cosine Transform...
Power lines constitute a great thread for aircraft flight safety. Digital camera based methods consider these power lines as digital lines and edges which are desired to be detected using line and edge detectors. EDLines, LSD and Hough Transform are the best line detection methods that are known in the literature. In this study, in order to determine the power lines for aircraft safety, methods of...
Local feature matching is one of the most fundamental issues in computer vision. Hierarchical agglomerative clustering (HAC) has been effectively used to distinguish inliers from outliers. The drawback of HAC is its large computational complexity which increases rapidly as the number of feature correspondences increases. To overcome this drawback, this paper proposes a region-constrained feature matching...
In this paper a bottom-up approach for detecting and recognizing objects in complex scenes is presented. In contrast to top-down methods, no prior knowledge about the objects is required beforehand. Instead, two different views on the data are computed: First, a GIST descriptor is used for clustering scenes with a similar global appearance which produces a set of Proto-Scenes. Second, a visual attention...
A common problem in wide-baseline stereo is the sparse and non-uniform distribution of correspondences when using conventional detectors such as SIFT, SURF, FAST and MSER. In this paper we introduce a novel segmentation based feature detector SFD that produces an increased number of 'good' features for accurate wide-baseline reconstruction. Each image is segmented into regions by over-segmentation...
Rail track extraction from the image can be used to determine the train localization, or vision-based inspection of the rail, and some other driver supporting systems in railway. For the vision-based inspection, it is one of the most important tasks. But visual approach suffers from some common difficulties, the illumination change, shadow, weather effects, etc, which make the image processing for...
Registration of multi-sensor images is an important part of image fusion. Because of the gray difference existing in multi-sensor image pairs, the registration problem of multi-sensor image is much difficult than that of single-sensor images. The existing STAR algorithm is appropriate for affine multi-sensor images, but is only applicable to images containing plenty of line segment features, because...
In this paper, we present a holistic approach to enable mobile robots using video projection in a situation aware and dynamic way. Therefore, we show how to autonomously detect wall segments that are suitable to be used as projection target in a dynamic environment. We derive several quality measures to score the wall segments found in the local environment and show how these scores can be used by...
Visual place recognition is a mature field in mobile robotics research. Recognizing places in datasets covering traversals of hundreds or thousands of kilometres and accurate localization in small and medium size environments have been successfully demonstrated. However, for real world long term operation, visual place recognition has to face severe environmental appearance changes due to day-night...
Canny Edge Detector is the most widely used operator for edge detection. The problem with Canny is that it outputs a binary edge map, where an edge pixel (edgel) is marked (e.g., its value in the edge map is 255) and a non-edge pixel is unmarked (e.g., its value in the edge map is 0). A typical binary edge map is of low quality, consisting of gaps, notch-like structures, ragged and multi-pixel wide...
We proposed a novel straight line detection method that can exclude line segments belonging to curved lines and integrates line segments of the same straight line. The proposed method links the edge pixels into strips and segments each strip into a series of line segments. Then the line segments are exploited to split the strips into strip fragments without turning points and then identify candidate...
In this paper, we propose a novel line segment detector, named as NETLines, which can produce a set of accurate line segments and a set of node-connected line-networks formed by connection of the line segments and the image boundary. Based on the line segments generated by other line segment detectors (e.g., EDLines [1]) on an edge map, the proposed algorithm efficiently makes use of the gradient...
The goal of this work is to recover road networks from aerial images. This problem is extremely challenging because roads not only exhibit a highly varying appearance but also are usually occluded by nearby objects. Most importantly, roads are complex structures as they form connected networks of segments with slowly changing width and curvature. As an effective tool for their extraction, we propose...
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