Developing A Parallel Program For Image Similarity Search Using Hashing Methods

Nowadays, images play an essential role in people’s lives as they document their memories and affairs. Therefore, a large number of images have been generated in different storage. As a result, there was a need to search for similar images in this colossal quantity. While enormous data processing requires speed in execution, it needs the parallel processing method. This study aims to develop a program to search for similar images using the image hashing methods, the Average Hashing, and the Difference Hashing, then to compare their performance. In addition, it aims to explore the effect of using parallelization on the speedup and efficiency of the program. The first part’s results stated that the performance of the Average Hashing and the Difference Hashing methods was affected by the type of data used, despite their effectiveness in detecting identical images. As for the second part, the parallel program reduced the execution time by almost half using two workers, while the best speedup value was when using eight workers. In terms of efficiency, it achieved the highest results with a value greater than 0.9 when using two workers.