Color Transfer Algorithm for Interior Design Based on Deep Learning

It is suggested that a topologically informed colour transfer method for interior design be used to match areas that have significant colour variability and colours that are just moderately rich. First, the image of the interior design is segmented, then the topology complete information of each region is calculated, and last, the region-matching relationship is determined based on the topology in order to improve the accuracy of the colour transfer; Second, colour is transferred between matched zones, and colour correction is applied to areas that do not get colour input in order to enhance the color's integrity as it is transferred; In conclusion, the algorithm for colour harmony works to improve colour harmony after the colour transfer by lowering the amount of noise. According to the findings of the experiments, the algorithm is able to keep the image's rich colour throughout while also improving the matching relationship and making colour adjustments locally, which leads to better colour transfer results. Targets can be captured and tracked with TOP technology. The use of neural networks and deep learning allows ambient perception to train and self-play the network, allowing it to continually update and locate the optimal grid path. The method of vertical falling grabbing is utilised in order to obtain and determine the quickest path to return to the grid in order to complete the procedure.