[May 2012]                Land Mine Detection and Image Processing                                          By            ...
Type       APN       ATM         UXOLandmine-detection: Traditionally            Weight    100g~4    6kg~11      Variousth...
image statistics (mean and standarddeviation) of the image [2].• Edge detection and grouping:Straight or partly circular e...
matrix then put values of surrounding(of noisy pixel) pixels in single dimarray with the repetitive valuesaccording to the...
system, similar to a text search engine   6. Wilhelm Burger, Mark J. Burge,but different in input method. We are         “...
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Land Mine Detection and Image Processing

  1. 1. [May 2012] Land Mine Detection and Image Processing By Ankush Srivastava [Email: anksrizzz@gmail.com, anksri000@gmail.com]Abstract: Landmines are causingenormous humanitarian and Introduction: Landmines are causingeconomic problems in many countries enormous problems in a large numberall over the world. Experts estimate of areas throughout the world todaythat up to 110 million landmines need [1]. Landmines are a significant causeto be cleared and more than 20,000 of suffering in many developingcivilians are killed or maimed every nations. They pose a great threat toyear by landmines, with many of the individuals for years after conflict hasvictims being children [11]. However, ceased and can be a seriouslandmine detection and clearance impediment to industrial andhave turned out to be an extremely agricultural development [8]. Therechallenging problem. At the current are more than 100 million mines inclearance rate, it will take about 1,000 more than 70 countries [7]. As per asyears to remove all landmines that are their purpose, mines can be classifiedalready placed and for every landmine into three types, antipersonnel minecleared, further 20 are being buried. (APM), antitank mine (ATM), andTherefore it is urgent to develop a unexploded ordnance (UXO).safe and cost efficient landminedetection system. In the past fifteenyears, various techniques, includingacoustic sensor, infrared technique,image processing techniques havebeen investigated [10]. Landminedetection with passive infraredimages can depend quite heavily onthe environmental conditions, andthere are cross over periods when thethermal contrast is negligible and themines may be undetectable. Thiswork we deal with land minedetecting through image processing.Valuable information can be hidden inthe images.
  2. 2. Type APN ATM UXOLandmine-detection: Traditionally Weight 100g~4 6kg~11 Variousthere are two methods for detecting kg kghidden landmines: prodding and Size 6~15cm 13~40c Variousremote sensing. In prodding, a probe (diamete mis gently inserted into soil to examine r)the existence of a buried object. Target Human Vehicle None intentionaRemote sensing is the other l, but canmethodology in which the presence of be anyan unexpected object on or thingunderneath the surface is examined Case Plastic Plastic, Mostlyusing sensors such as electromagnetic Material Metal metalinduction sensors (EMI), X ray Detonata 500g 120kg Unpredictbackscatter radiography, ground ble able Pressurepenetrating radar (GPR), infraredcameras (IR), and thermal neutron Imageanalyzers [4].It is important to understand theextent to which the design of mine [12]. Signal processing for landminedetection and minefield delineation detection seeks to exploittechnology is based on military discrimination information inoperational doctrine, compared to measured signals from a variety ofhumanitarian or post-conflict sensors. Signals used in minerequirements [3]. detection are generallySignal processing is a necessary, multidimensional [9]. The goal of thisfundamental component of all work is to detect and locate landdetection systems and can result in mines on the earth surface usingorders of magnitude improvement in image processing. This mechanismthe probability of detection and transfers low level imagereduce the false alarm rate of almost characteristics into high levelany sensor system. semantic features using image processing algorithms.Landmine-detection and ImageProcessing: Image plays vital role in Landmine-detection concept:-every aspect of business such as • Color and intensity analysis:business images, satellite images, Detection is based on object color ormedical images and so on. If we intensity contrast with theanalysis these data, which can reveal surrounding background. Theuseful information to the human users contrast threshold is defined by local
  3. 3. image statistics (mean and standarddeviation) of the image [2].• Edge detection and grouping:Straight or partly circular edges areextracted because they can indicateartificial objects. The subsequent stepgroups edges into hypotheticalartificial objects [2].• Polarization analysis: Objects aredetected based on their polarization Histogramcontrast with the surrounding Median Filter: In median filtering,background [2]. first we sort the surrounding pixels ofRegardless of the type of sensor, noise desired pixel behalf of its intensityis always present [7]. For reducing value then desired pixel will bethese types of noise we use various replaced by middle element of sortedtypes of filters. pixel values [5][6].Some neighborhood operations workwith the values of the image pixels inthe neighborhood and thecorresponding values of a sub imagethat has the same dimensions as theneighborhood. The sub image is calleda filter [5].In this work we introduce twofiltering methods; Median Filter and Applying Median AlgorithmWeight Median Filter; for removingthe noise. HistogramOriginal image received from sensor devices Weight Median Filter: In weight median filter, first we create weight
  4. 4. matrix then put values of surrounding(of noisy pixel) pixels in single dimarray with the repetitive valuesaccording to the values of weightmatrix and sort it after that noisypixel is replays by the middle elementof the sorted array which full of pixelvalues [6]. Original image received from sensor devicesApplying Weight Median Algorithm Threshold image; where threshold value is 170. Sensor Devices Images Image threshold Noise ReductionHistogram ResultThreshold Method: In this sectionwe introduce a new mechanism fordetecting the landmine. In this Usermechanism, we simply converting theGary scale and color images into Block Diagram of the systembinary or black/white images with Conclusion: This paper is an outcomespecific threshold value or it may be of the study, that a landmine detectionvary. It is also known as image system which can be viewed as anthreshold. interactive system with a user responsible to make queries to the
  5. 5. system, similar to a text search engine 6. Wilhelm Burger, Mark J. Burge,but different in input method. We are “Principles of Digital Imagefocuses on the image processing for Processing”.detect the landmine on the earth 7. Cheolha Pedro Lee, “Minesurface. Various types of sensor Detection Techniques Usingdevices capture the images of the land Multiple Sensors”.surface, and the noise is always 8. Peter Torrione, and Leslie M.presents. For this purpose we applied Collins, “Texture Features Fortwo image processing algorithms that Anti-Tank Landmine Detectionis, Median Filter and Weight Median Using Ground Penetrating Radar”.Filter, to reduce the noise. We also 9. Paul Gader, “SIGNAL-PROCESSINGintroduce new technique for detecting AND SENSOR FUSION METHODS”.the land mine that is image threshold 10. Yijun Sun and Jian Li, “Adaptivemethod with the specific threshold Learning Approach to Landminevalue. Detection”. 11. “Adopt-a-minefield,References:- http://www.landmine.org,” 2000.1. Renbiao Wu, Jiaxue Liu, Tang Li, 12. A. Kannan, Dr. V. Mohan, Dr. N. Qian Gao, Hongyu Li, and Bei Anbazhagan, “Image Clustering Zhang, “Progress in the Research and Retrieval using Image Mining of Ground Bounce Removal for Techniques”. Landmine Detection with Ground Penetrating Radar”.2. Dr. John G.M. Schavemaker, Dr. Wim de Jong, Ir. Marcel Breuers, Ir. Jan Baan, “Development of Camera System for landmine detection”.3. L. van Kempen, A. Katartzis, V. Pizurica, J. Cornelis and H. Sahli, “Digital Signal/Image Processing For Mine Detection”.4. Najjaran, H.; Goldenberg, A.A., “Landmine detection using an autonomous terrain scanning robot”.5. Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing”.