Study On Multiple Sub-pattern Image Representation And Retrieve Methods Based On NAM

Image representation methods play an important role in computer graphics,imageprocessing,pattern recognition,computer vision and robotics.With the concept ofpacking problem,a non-symmetry and anti-packing pattern representation model(NAM)is presented and the general representation method is given for various kinds of patterns.Based on Non-symmetry Anti-packing pattern representation Model(NAM),twokinds of NAM image representation method are presented,i.e.based Multiple sub-patternNon-symmetry Anti-packing representation Model(MNAM) including Multi-DirectionNon-equilateral right-angled triangle and based Polygonal Non-symmetry Anti-packingrepresentation Model(PNAM).A fast moments compute method based NAM ispresented,firstly apply NAM to the image content retrieval,in addition to giving a imagecomtent retrieval method based on the MNAM and PNAM's color and shape character.On the basis of analyzing the represent efficiency of NAM,one kind of multiplesub-pattern image representation(MNAM) includeing several typical sun-pattern such asdot,line,triangle and rectangle is defined.Based on the define,the triangle patternincluding four kinds of direction non-equilateral right-angled triangle.the experimentalresults proves that MNAM is better that the LQT and RNAM on image compress andimage rebuilding.Aim to MNAM introduce Interpolation method,redifine the four kinds of pattern,i.e.dot,line,rectangle and triangle.Based on the locations and gray value of threepoints,linear interpolation method can calculate the gray value of any point in the area.The theoretical analysis and the experimental results show that the algorithm complexityis increased,image compression ratio decreased slightly,but the quality of imagereconstruction has a marked improvement after introducing the interpolation method.With respect to the lossless image representation,a novel NAM image representationmethod based on the Polygon subpattern is proposed,which is named PNAM.PNAM applies polygon searching algorithm based on regional growth to encoding image.And arelatively compact shape grammar method is designed for storaging polygon.Animproved algorithm for edge logo is proposed for image reconstruction.Analyzing timeand space complexity of these algorithms and the data of encoded images,Experimentsshow that PNAM has very good performance for image compression ratio and imagequality.A fast calculation method on relatively complex Legendre moment is proposed.Baseon MNAM and PNAM,images after coding can be seen as a number of blocks having thesame gray value.Using Green formula,which replaces integrals on 2-dimensions spaceby integrals on 1-dimension.And When the border is expressed as a polygon,the lineintegral can be directly calculated from the Vertex,which further simplifies thecalculation process on Legendre Moment.Finally,a both effective and suitable fastmoment calculation for binary and gray-scale image is proposed.The experiments showthat that this method plays a significant role in improving the computing speed.The research analyses the limits of image retrieval,which is that the retrievalactually depends on text keyword.So a novel image retrieval method based on NAM isproposed.The novel method could have a good performance at the color and shape-basedretrieval.The algorithm of the NAM for color-based image retrieval is presented and analysisits Complexity.Finally,experiments show that it is effective.The algorithm includes twoprocesses that is extraction of gray-scale histogram and histogram matching.TheNAM-based approach replaces an image by a sub-model queue.The queue has a fewernumber of nodes and a smaller amount of data compared with the pixelimage.Therefore,the proposed approach of image retrieval has a Lower time and spacecomplexity.Through testing a number of binary and gray scale images,the experimentaldata show that the algorithm is effective.A novel and effective approach about image retrieval using PNAM is proposed. Polygon generated by PANM is as the object of shape extraction,This paper presents anew method that is more intuitive and simple than the traditional method.And usingshape complexity,radius Variance and(?) -radius,A effective approach is proposed.Thepaper give the shape retrieval algorithms and analysis their time and space complexity.Finally,The experiments for two-valued and multi-value images show the algorithms areeffective.This method with a combination of the color-based retrieval described in detailin Chapter 5 will generate a better result.In a word,the proposed MNAM and PNAM approaches for the imagerepresentation and manipulations,as envisaged in this paper,shows a very strong promiseand has good potential in business applications dealing with image processing,such asreducing strong room,increasing transmission speed,and improving content based imageretrievel efficiency.