An Automatic Bridge Detection Technique for Multispectral Images

Chaudhuri, Debasis; Samal, Ashok

doi:10.1109/tgrs.2008.923631

Cited by 81 publications

(28 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Because our segmented image is multi-level clustered image (as the number of clusters), we have implemented a specialized recursive scanning algorithm 17 that is fast and efficient for our application. In our recursive scanning method, we begin by selecting a pixel with label 1 (say cluster number 1) and label it is 'marked'.…”

Section: Region Removal Techniquementioning

confidence: 99%

Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images

Kushwaha¹,

Chaudhuri²,

Singh³

2013

DSJ

View full text Add to dashboard Cite

Automatic target detection like oil tank from satellite based remote sensing imagery is one of the important domains in many civilian and military applications. This could be used for disaster monitoring, oil leakage, etc. We present an automatic approach for detection of circular shaped bright oil tanks with high accuracy. The image is first enhanced to emphasize the bright objects using a morphological approach. Then, the enhanced image is segmented using split-and-merge segmentation technique. Here, we introduce a knowledge base strategy based on the region removal technique and spatial relationship operation for detection of possible oil tanks from the segmented image using minimal spanning tree. Lastly, we introduce a supervised classifier, for identification of oil tanks, based on the knowledge database of large amount data of oil tanks. The uniqueness of the proposed technique is that it is useful for detection bright oil tanks from high as well as low resolution images, but the technique is always better for high-resolution imagery. We have systematically evaluated the algorithm on different satellite images like IRS -1C, IKONOS, QuickBird, and CARTOSAT -2A. The proposed technique is detected bright structures but unable to detect the dark structure. If the oil tank structures are bright relative to the background illumination in the image then the detection accuracy by the proposed technique for the high resolution image is more than 95 per cent.

show abstract

Section: Region Removal Techniquementioning

confidence: 99%

Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images

Kushwaha¹,

Chaudhuri²,

Singh³

2013

DSJ

View full text Add to dashboard Cite

show abstract

“…Bridges have no standard structure that can be considered it vary from each other in many aspects whether it have piers, cables etc. Chaudhuri and Samal (2008) used knowledgebased method by defining a set of rules for initial classification of the multispectral images of bridges into eight land-cover types (Chaudhuri and Samal, 2008). The technique commonly known as 'supervised classification' is done at three levels.…”

Section: Introductionmentioning

confidence: 99%

Isotropic surround suppression and Hough transform based target recognition from aerial images

Munawar

2017

Int. j. adv. appl. sci.

View full text Add to dashboard Cite

In this paper a procedure for target recognition of linear shaped landmarks (bridges and runways) from optical imagery is proposed. This study has done to propose a method for efficient target recognition as there is a need to have surveillance measures for defense, trade and disaster management. Keeping this in view, in this study image segmentation is performed using canny edge detection technique. Edge maps with more texture environs are suppressed by means of introducing a way that can combat isotropic surround. The inhibitor should apply lesser weights on the edges in case of texture environs as compared to the edges having defined boundaries. An efficacious method of computation for calculations of the isotropic surround suppression is used that accelerates the proposed algorithm. Subsequently, Hough transform is used on edge image along with its suppressed energy to extract all possible lines. Finally, the target regions are segmented from surrounding regions by examining geometric information and the resemblance between target and its surroundings. A number of the existing methods have been viewed and explored; the final proposal is refined to match the current trends and needs. The results indicate that the new method is efficient and effective for extracting target in optical images acquired by Unmanned Air Vehicles and it improves target detection significantly.

show abstract

“…Most of these methods aim on the detection of roads [10][11][12], while only a few have been developed for the detection of other features (e.g., linear woody vegetation [13], bridges [14], rivers [15]). Although most of these methods can be usually adapted to the delineation of rivers, they are mostly not fully automatic.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised river detection in RapidEye data

Klemenjak

Waske

Valero

et al. 2012

2012 IEEE International Geoscience and Remote Sensing Symposium

View full text Add to dashboard Cite

Remote sensing is a widely-used utility in supporting multilateral environmental treaties such as the Water Framework Directive (WFD). Regarding the WFD most remote sensing applications aim on the assessment of the biochemical status of surface water, while the general detection of water networks is disregarded. Therefore, a methodology for the automatic extraction of river networks from multispectral satellite data is presented.Moreover, a new index called RE-NDWI is introduced, which highlights open water bodies in optical remotely sensed data, using the red edge and green band.The river detection method is tested on RapidEye data from three test sites in Germany and clearly outperforms a regular, supervised SVM-classification.

show abstract

An Automatic Bridge Detection Technique for Multispectral Images

Cited by 81 publications

References 12 publications

Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images

Automatic Bright Circular Type Oil Tank Detection Using Remote Sensing Images

Isotropic surround suppression and Hough transform based target recognition from aerial images

Unsupervised river detection in RapidEye data

Contact Info

Product

Resources

About