TAILIEUCHUNG - Humanitarian Demining Part 7

Tham khảo tài liệu 'humanitarian demining part 7', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | GPR Environmental-Based Landmine Automatic Detection 171 association Yen 1999 . If there is an association then there is a PMN2 landmine and its depth is the output fuzzy rule. If there is no association for any of the features it means that the object is not the specified PMN2 landmine. MD feature GPR feature Fuzzy fusion rule base Fuzzy rule base association decision making system Features positions Decision Fig. 23. Decision making system Performance The The proposed algorithm could easily classify the first object the dummy land mine and expect its depth to be around cm its surface was actually at a depth of cm . The second object a case with an inserted metal bolt as well as the third object a metal bolt only could be classified as a non-land mine object. The second object was detected as a land mine suspect with GPR but not a land mine suspect with MD. There was no association of the MD feature. Also the third object was not detected as a landmine suspect with either MD or GPR. There was no association of both MD feature and GPR feature. The fulfillment of the decision making conditions as well as the final decision are shown in Table 3 where O means the condition is fulfilled and X means the condition is not fulfilled. The decision of the second and third object would be difficult if it to be done by a deminer from GPR images and or MD sounds or images . It should be noted here that even though the MD feature of the 2nd object Table 3 was not fulfilled by the decision making system MD will give a sound or image . Also even though the GPR feature of the 3rd object Table 3 was not fulfilled by the decision making system it will give an image. The features were not fulfilled because their values were outside the range leant during the learning phase. Based on that the proposed automatic detection algorithm will decrease the false alarm rate significantly. One limitation of the algorithm is that it is based on the association of the input fuzzy .

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