<b>Abstract</b>— <p>With the rapid progress of information technology, information has evolved from its original textual form to a rich and diverse form of internet information. It is fully reflected in smart home applications in the intuitive form of images. However, image search in smart homes is a real-time process. Existing systems cannot meet the requirement for users to receive responses in a short period of time. Therefore, in response to the long system response time, long image processing time, and low retrieval accuracy, an image search system based on parallel computing of the central processor is proposed for application in smart home design. Firstly, the image area is segmented and preprocessed. Secondly, a multilevel edge detection algorithm for parallel computing between the central processing unit and graphics processor is designed. Finally, an image search system with parallel computing between the central processing unit and graphics processor is established. The research results indicate that the increase in central processing unit running time is the most significant, increasing from 0.18 to 1.28, with a growth rate of 1.1. The growth rate of graphics processor runtime is relatively small, increasing from 0.05 to 0.17, with a growth rate of 0.12. As the image size increases, the overall computational complexity also increases. The parallel acceleration performance of graphics processors and central processing units is gradually becoming significant.</p>