| Summary: | 碩士 === 國立高雄第一科技大學 === 電腦與通訊工程所 === 95 === In this thesis, a content based image retrieval system using hardware/software co-design on a programmable logic component is presented. In this work, we use generalize Hough transform (GHT) to integrate block information within an image for measuring similarity values. A large amount of block matching tasks are involved in the GHT. Actually, the block matching module spends most of the execution time for answering a query. In addition, each block (or visual pattern) of a visual query object can perform its block matching procedure to find the possible match blocks in database images individually. The system implicitly contains a large number of fine-grained parallel units. Thus, it is suitable to be implemented with a hardware architecture in order to achieve the goal of real-time image retrieval.
In this work, we propose a systolic-like parallel architecture consisting of a two-dimensional array of process elements (PE). Each PE contains several computing units (CU) and each CU performs a block matching task. All the CUs do the block matching at the same time, so the retrieval speed of the system is fast. Furthermore, we use a block memory to accumulate votes of the global geometric transformation parameters in the GHT. The peaks of votes of the global geometric transformation parameters extracted from the block memory are finally transmitted to the master unit, which is used to calculate the similarity value between a query image and a database image and returns the relevant images to the user. In order to speed up the design and implement of the system, some silicon intellectual properties are used in our system.
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