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008 131021t2013 my da f abm 000 0 eng d
020 _aTHE0006008(Local)
039 9 _a201905151115
_baida
_c201710121618
_daishah
_y201310211528
_znabilah
040 _aUMP
090 _aTE223 .R85 2013 rs Thesis
100 1 _aRui, Xiao
245 1 0 _aLane markings detection based on e-maxima transformation and improved hough /
_cRui Xiao
260 _aKuantan, Pahang :
_bUMP,
_c2013
300 _axiii, 93 p. :
_bill. ;
_c30 cm. +
_e1 CD-ROM
502 _aThesis (Master of Engineering (Electronic)) -- Universiti Malaysia Pahang – 2013
504 _aBibliography : p. 86-92
520 3 _aAccording to Malaysians Unite for Road Safety (MUFORS) online survey, human error, for example, improper vehicle deviation or unintentional lane change is one of the main causes of traffic accident. Lane shift in traffic can be complex and dangerous. This study aims at developing a fast, low-cost, and sophisticated system with the ability to detect unexpected lane changes that may reduce the probability of a vehicle straying out of lane. Various road models to identify the lanes have been explored including straight-line, B-snack, linear-parabolic model, and deformable model. Most lane models, either simple or lack of flexibility or complex, may cause heavy computation in processing the time needed. The feature of roadway has certain degree of curvature and constraints, for instance, no sudden road turn is the design for road safety driving. A short segment of a long curve with a relatively low curvature is approximated as a straight line, based on this point, the important contribution of this thesis presents a lane detection algorithm using E-MAXIMA transformation and improved Hough transform which is the algorithm with great efficiency, high robustness and also at low cost to detect road lane markings. First of all, the region of interest from input image to reduce the searching space is defined; then the image into near field-of-view and the far field-of-view is divided. In the near field-of-view, Hough transform will be applied to detect lane markers after image noise filtering and lane features extraction by E-MAXIMA. The experimental results based on collected video data under complex illumination conditions had proved that the proposed algorithm is able to detect the road lane marking efficiently achieving a correction rate of 95.33%. The process time on average is 32 ms/f, namely every second can deal with 31.25 frames that demonstrate superior and robust results compared to other existing methods. To conclude, the work done in this thesis may apply to autonomous driving navigation and driving security assistance. The potential of such a system is further linked to the system with the vehicles’ turn signal, whereby the system will be able to detect an unintentional drift out of the lane.
650 0 _aTraffic accidents
650 0 _aAccident prevention
650 0 _aRoads
_xDesign and construction
856 4 0 _uhttp://ecollib.ump.edu.my/3767/
_zLibrary access only
999 _aVIRTUA40
_c4125
_d4131
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*8560*9992