01741nam a22001817a 4500999001700000082001300017100006400030245007300094250001700167260002800184300000800212500106300220700004101283856003201324942001101356952009001367952010201457  c64774d64771  aR/IMS-19  aNajim uddina14MSIT15aSupervisor - Dr. Fareed Ahmed Jokhio  aA Hybrid Approach for Efficient Content Based Image Retrrival System  a14-MS(IT)-15  aNawab shahbQUESTc2019  a31p  aABSTRACT

In this thesis performance of image matching techniques is analyzed. Here two existing techniques i.e. scale-invariant feature transform (SIFT) and Speeded up robust features (SURF) are used to develop a HAECBIR technique. Performance of these three technique is analyzed by using Oxford building dataset. The data set consist a set of different image classes. These techniques are used to extract visual features of images. Frequency vector is recorded a Histogram for spatial tile of the image. The resulting vector are used for feature matching with other images the performance with respect to accuracy and time is evaluated for these three techniques. The result Indicate that matching accuracy of the Hybrid technique is better than SIFT and SURF. The hybrid approach is also faster than SIFT in terms of execution time to retrieve similar images from dataset.
Keywords: Feature Extraction, A hybrid Approach Efficient Content based Image retrieval system (HAECBR), Speeded up robust features (SURF), Scale Invariant feature transform (SIFT)
  aDepartment 0f Information technology  uhttp://tinyurl.com/mrtj65ef  cTHESIS  00104070aRESEARCHbRESEARCHd2019-07-01l0pMP/43-496r2019-07-01 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2023-12-20l0pMP/53-663r2023-12-20 00:00:00w2023-12-20yTHESIS