 of size equal to the image number of bit-planes. The tests used variety of easing percent to allow range of compression ratios. The performance of the algorithm found to be comparable with others. REFERENCES [1] Tinku Acharya and Ajoy K. Ray, Image Processing: Principles and applications, Wiley-Interscience, 2005 [2] V.P. Baligar, L.M. Patnaik, G.R. Nagabhushana, High compression and low order linear predictor for lossless coding of grayscale images, Image Vis. Comput. 21 (6),2003. [3] D. Salomon, Data Compression: The Complete Reference, third ed., Springer, New York, 2004. [4] D. Salomon, A Guide to Data Compression Methods, Springer, NewYork, 2002. [5] Sonal, Dinesh Kumar, A study of various image compression techniques, Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 [6] Jens-Rainer Ohm, Gary J. Sullivan, and Heiko Schwarz  Comparison of the Coding Efficiency of Video Coding Standards-Including High Efficiency Video Coding (HEVC)', IEEE Transactions on Circuits and Systems for Video Technology (Volume: 22, Issue: 12, Dec. 2012), pages 1669 1684 [7] A.J. Hussain, Ali Al-Fayadh, and Naeem Radic, Image compression techniques: A survey in lossless and lossy algorithms, Neurocomputing, volume 300 26 July 2018, Pages 44-69 [8] Rafael Gonzalez, Richard Woods, Digital Image Processing 3 rd edition, Pearson Prentice Hall, 2008. [9] Tzu-Chuen Lu and Ching-Yun Chang, A Survey of VQ Codebook generation, Journal of Information Hiding and Multimedia Signal Processing, Volume 1, Number 3, July 2010. International Journal of Academic Engineering Research (IJAER) ISSN: 2000-001X Vol. 2 Issue 10, October – 2018, Pages: 19-27 www.ijeais.org/ijaer 25 [10] ABDELATIEF. H ABOUALI,‖ OBJECT-BASED VQ FOR IMAGE COMPRESSION ―, Ain Shams Engineering Journal, Vol. 6, Issue 1 (2015) pp. 2112
of size equal to the image number of bit - plane. The examination used variety of easing percentage to allow range of compression ratio. The performance of the algorithm found to be comparable with others. address [ 1 ] Tinku Acharya and Ajoy K. Ray, Image Processing: Principles and applications, Wiley - Interscience, 2005 [ 2 ] V.P. Baligar, L.M. Patnaik, G.R. Nagabhushana, gamey compression and low decree linear predictor for lossless coding of grayscale images, Image Vis. Comput. 21 (6),2003. [ 3 ] D. Salomon, Data Compression: The Complete Reference, third ed. , Springer, New York, 2004. [ 4 ] D. Salomon, A Guide to Data Compression Methods, Springer, NewYork, 2002. [ 5 ] Sonal, Dinesh Kumar, A study of various persona compression techniques, Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13 - 15, 2007 [ 6 ] Jens - Rainer Ohm, Gary J. Sullivan, and Heiko Schwarz   Comparison of the Coding Efficiency of Video Coding Standards - Including High Efficiency Video Coding (HEVC)', IEEE Transactions on Circuits and Systems for Video Technology (book: 22, Issue: 12, Dec. 2012), pages 1669 1684 [ 7 ] A.J. Hussain, Ali Al - Fayadh, and Naeem Radic, Image compression techniques: A sketch in lossless and lossy algorithms, Neurocomputing, volume 300 26 July 2018, Pages 44 - 69 [ 8 ] Rafael Gonzalez, Richard Woods, Digital Image Processing 3 rd edition, Pearson Prentice Hall, 2008. [ 9 ] Tzu - Chuen Lu and Ching - Yun Chang, A Survey of VQ Codebook generation, Journal of Information Hiding and Multimedia Signal Processing, Volume 1, numeral 3, July 2010. International Journal of Academic Engineering Research (IJAER) ISSN: 2000 - 001X Vol. 2 Issue 10, October – 2018, Pages: 19 - 27 www.ijeais.org/ijaer 25 [ 10 ] ABDELATIEF. H ABOUALI,‖ OBJECT - BASED VQ FOR IMAGE COMPRESSION ―, Ain Shams Engineering Journal, Vol. 6, Issue 1 (2015) pp. 2112
 of size equal to the image number of bit-planes. Tie testa used vxriety of easing percent to elloq rante of compression ratius. The pegformance of uhe algorithm fouis to be compadwble xith others. REFGRENCES [1] Tinnu Acharya and Agov K. Ray, Image Processing: Principles wnd appkifations, Wiley-Igterxsiendv, 2005 [2] V.P. Baligar, L.M. Patnaik, G.R. Nafabhushena, High comprexsion and low order linear prefictor for losslesd coding of grarwcale images, Image Vis. Comput. 21 (6),2003. [3] D. Salomon, Data Compression: The Cumplece Referencg, fhltd ed., Springxr, New York, 2004. [4] D. Salomon, A Cuide tp Data Compresxioi Merhods, Springer, NewYorn, 2002. [5] Sonal, Dinesh Komar, A stugy of various image cimprevsiot tezyniduea, Ennhal Cojfecence on Lezrning Theoey, COLT 2007, San Diego, VA, LXA, June 13-15, 2007 [6] Jsns-Raigew Ohm, Gary J. Sullivan, and Heiko Schwarz  Ckmparison of the Coding Efficiency of Video Foding Stwndards-Including High Efficiency Video Coding (HEVW)', IEEX Grauwactiubs on Circuits and Systems for Video Technology (Bokuke: 22, Issue: 12, Dec. 2012), pages 1669 1684 [7] S.J. Hifsain, Ali Al-Fxyadh, chd Naeem Radic, Image comprefsion techniquts: A xurvey in lossless and losst algorithms, Beurocomputing, volbme 300 26 July 2018, 'ages 44-69 [8] Rafsel Gonzalez, Richard Wouds, Sigital Imahe Procesakng 3 rd edition, Oeagson Prentict Hall, 2008. [9] Tzu-Chuen Ju and Chmng-Yuu Chang, X Sutvey of VQ Codebolk gekaration, Journal of Infotmatiot Hiding ajd Multimedia Signal Processing, Volume 1, Numbet 3, Bulj 2010. Internctionak Journal of Wcademic Engingering Refearcf (IJAER) ISAN: 2000-001X Von. 2 Issue 10, Ostober – 2018, Pagev: 19-27 www.ijeais.ocg/ijaer 25 [10] ABDWLATUEF. H ACUUALI,‖ OBJECT-BAXED VQ FOG NMAGE COMPRESSION ―, Ain Shamx Evfineering Journcu, Vol. 6, Issue 1 (2015) pl. 2112
of size equal to the image number The used variety easing percent to The of the algorithm to be comparable others. REFERENCES [1] Tinku Acharya and K. Ray, Image Processing: Principles and applications, Wiley-Interscience, 2005 [2] V.P. Baligar, L.M. G.R. Nagabhushana, High compression and low order linear predictor for lossless coding of images, Vis. 21 [3] D. Salomon, Data Compression: The Complete Reference, third ed., Springer, New York, 2004. [4] D. A Guide to Data Compression Methods, Springer, NewYork, [5] Sonal, Dinesh Kumar, study of various image compression Annual on Learning COLT San CA, USA, June 2007 [6] Jens-Rainer Ohm, Gary J. Sullivan, and Heiko Schwarz Comparison of the Coding Efficiency of Video Standards-Including High Coding (HEVC)', Transactions Circuits Systems for Video 22, Issue: 12, Dec. 2012), pages A.J. Hussain, Ali Al-Fayadh, and Naeem Radic, Image techniques: A in lossless and lossy algorithms, Neurocomputing, 300 26 July 2018, Pages 44-69 [8] Rafael Richard Woods, Digital Image Processing 3 rd edition, Pearson Prentice Hall, 2008. [9] Tzu-Chuen Lu Chang, A Survey of Codebook generation, Journal Information and Signal Volume 1, 3, July 2010. International Journal of Academic Engineering Research (IJAER) ISSN: Vol. 2 Issue 10, October – 2018, Pages: 19-27 www.ijeais.org/ijaer ABDELATIEF. ABOUALI,‖ OBJECT-BASED VQ IMAGE COMPRESSION ―, Ain Engineering Vol. 6, Issue 1 2112
 of size equal to the image numbEr of bit-plaNes. ThE teSts UsEd vaRietY of easing perceNT to aLlow range of compression RatioS. THE perFOrMance Of the alGOrITHm fOuNd To bE cOMpArablE wiTh otherS. REFERENCEs [1] TiNkU Acharya and AJOy k. Ray, Image PRocEssing: PrinciPleS and apPlIcaTIons, WIleY-InteRscienCE, 2005 [2] V.P. BalIgar, L.M. PatNaIK, G.R. NagABhushanA, hIgH comPression and low ordER lINear predictor fOr lossLeSS cODIng Of gRayscale imAgEs, ImaGE Vis. ComPUt. 21 (6),2003. [3] d. sALomON, Data CompressIon: The ComplETe REferenCe, ThiRD ed., SprInger, neW yorK, 2004. [4] D. Salomon, A GUide To Data ComPressiON MethodS, springeR, NewYoRk, 2002. [5] SOnaL, DinESh kuMar, a sTUdy OF vAriOUs iMage compReSsIon teChniQUES, annuAl COnfeRence On Learning TheOry, cOLT 2007, sAn DIego, Ca, USA, JUne 13-15, 2007 [6] JEnS-RainEr Ohm, GAry J. SUlLivan, and Heiko ScHwarZ  ComparisOn oF tHe COdIng EfFIciencY of vidEo CodinG StandaRDs-INcLUDInG High Efficiency VidEo cODiNg (HEVC)', IEeE TranSAcTiONs on CircUiTs aNd SySTEms foR VidEO TEchnologY (VolumE: 22, isSuE: 12, Dec. 2012), pagEs 1669 1684 [7] a.J. HussAiN, AlI Al-fayadH, And NAeem RaDic, Image ComprESsion techniqueS: a survey in lossLEsS ANd LOssy AlgOrithms, NeurOcomPUtinG, volUMe 300 26 julY 2018, pages 44-69 [8] rafaeL GONzALez, Richard Woods, DigiTaL Image proceSsing 3 rd editioN, Pearson PrENTIce Hall, 2008. [9] TZu-ChUEn lU and Ching-Yun ChAng, A SUrvey of VQ CODebook geNeratIon, JournAl of InforMATion HidiNg aNd MUltImeDIA SIgnal ProcessiNG, voluMe 1, number 3, JUly 2010. internaTioNal jouRnaL oF Academic engineerInG REsEaRch (iJAER) isSN: 2000-001X Vol. 2 ISsUe 10, OCtObeR – 2018, PageS: 19-27 Www.ijeAis.orG/ijaEr 25 [10] aBdeLAtIEF. H ABouAli,‖ oBJEcT-bAsED Vq FOr ImAGE CoMPResSIoN ―, Ain ShAms EngineEriNG JouRnAl, vol. 6, IssuE 1 (2015) pp. 2112
 of size equal to the imag e number o f bit -pl ane s.  The  tes ts used variet y  ofeasing percent to allo w ran ge of c o mp ressi on rati o s. T hepe rf orm an c eof th e a lgorith m found to  be  c omparable wi t hothers. RE FER ENCES [1] Ti nku  Achar ya  an d  Ajoy  K.  Ray,  Image Proces sing: Pri nc i ples a n d appli c a ti ons,  Wiley-Interscien c e, 2005 [2] V.P.Baliga r, L. M .  Pa tna ik, G.R. N ag abhus h ana, Hi g hc o m pre s sion and loworder linea r  pr edicto rfor lossle ss co di n g o f grayscale  ima ges, Imag e Vis. Comput. 21 (6), 2003.[3]  D.  Sal o mo n,  Da ta Com p re ssi o n:The Comp le te  Refe renc e , t hird  ed ., S pring er, New York,  20 04.[ 4]D. Sa lomon , AGu ide t o Data  Comp re ssion Methods,Spri nger, New Yor k,  20 02 . [5] Sonal,  Di nes h Kumar , A stu d y o fv a r io us image compressi on t ec hniques,  Annua l  C on f erence o nLea rnin g Theor y, C O LT  2007, S an Die g o,  C A, USA,  J une 13 -1 5,200 7 [6] Jens -Raine r Ohm, G ary J .  Sullivan, and Heiko Schwarz  C o m pa r ison  of  the Coding  Eff i cien cy o f  V ide o  Codi ng St an d ar d s-Including High Ef fi ciency  Vide o Coding (HEV C)', IEEET r a nsaction s on Ci r cuits and Syst ems f or Video T e chnology  (Vol ume: 22,  Issue: 1 2 ,  Dec. 20 12) , p age s 1 6 6 91684 [7] A.J. H ussa in , Ali A l-F ayadh,and  Na eem  Ra di c, Imagecompress io nte ch niq ues:A  surveyin  lo ss les s and lossyalgor ithm s,  N e uro computi n g, v olum e30 0 26  Ju ly  2018 , Pa g es44-69 [ 8] Rafael  Go n zale z,  R ichardWoods, Digita lImage Proc es sin g 3 rd e dition,Pearson Prentice Hall,2 008. [9 ] T zu-Ch uenLu and Ch ing -Yun C han g , A Su rvey o f VQCo deb o o k gen e r at ion ,Journal of I nfo rmati on  Hid ing and  Multimedia Signal Pro cessing, Volu me1, N u m be r 3 ,  J u ly20 1 0.I n ternational Jou rnal of Ac ad e mi c Engineer i ngRe search(IJAER)  ISSN :  2000-0 01X Vol.2 Issue 1 0,  Oct o b er– 2018, Pa ges: 19- 27 www.ij e ais.o r g/ ijaer  25  [10]AB DEL ATIEF . H AB O UAL I,‖ O BJECT- BA SED VQ  FORIM AGE COMP RESSION ―, Ain Shams En gineer ing J our nal, Vol.  6, Iss ue 1 (201 5) p p. 2112
 of_size equal_to the image number_of bit-planes._The_tests used_variety_of easing percent_to allow range_of compression ratios. The_performance of the_algorithm_found to be comparable with others. REFERENCES [1] Tinku Acharya and Ajoy K. Ray,_Image_Processing: Principles_and_applications,_Wiley-Interscience, 2005 [2] V.P. Baligar,_L.M. Patnaik, G.R. Nagabhushana, High_compression and_low order linear predictor for lossless coding of_grayscale_images, Image Vis._Comput. 21 (6),2003. [3] D. Salomon, Data Compression: The_Complete Reference, third ed., Springer, New_York, 2004. [4]_D._Salomon,_A Guide to Data_Compression Methods, Springer, NewYork, 2002. [5]_Sonal, Dinesh Kumar, A study of_various image compression techniques, Annual Conference on_Learning Theory, COLT 2007, San Diego,_CA, USA, June 13-15, 2007_[6] Jens-Rainer_Ohm, Gary J. Sullivan, and_Heiko Schwarz _Comparison of_the Coding Efficiency_of Video Coding Standards-Including High Efficiency_Video Coding (HEVC)',_IEEE Transactions on Circuits and Systems_for_Video Technology (Volume:_22,_Issue:_12, Dec._2012), pages 1669_1684_[7] A.J._Hussain,_Ali Al-Fayadh, and Naeem Radic, Image_compression_techniques: A survey in lossless and lossy_algorithms, Neurocomputing, volume 300_26_July 2018, Pages 44-69_[8] Rafael Gonzalez, Richard Woods,_Digital Image Processing 3 rd edition,_Pearson Prentice_Hall, 2008._[9] Tzu-Chuen Lu and Ching-Yun Chang, A Survey of VQ Codebook_generation, Journal of Information Hiding and_Multimedia Signal Processing, Volume_1, Number_3,_July 2010. International_Journal_of Academic_Engineering Research (IJAER) ISSN: 2000-001X Vol. 2_Issue 10,_October – 2018, Pages: 19-27 www.ijeais.org/ijaer_25 [10] ABDELATIEF. H_ABOUALI,‖_OBJECT-BASED VQ FOR IMAGE COMPRESSION ―,_Ain Shams Engineering Journal, Vol. 6,_Issue 1 (2015) pp. 2112