Abstract
One of the most important and recurring tasks in managing a store is to provide accurate, up-to-date price information to customers on the shelves. Manual updating of price tags has been a time-consuming, error-prone task with high labor costs. An Electronic shelf labels (ESL) system is becoming an attractive alternative for this task because of the dynamic-price-updating and customer’s product-evaluation-display features. A common ESL system configuration in a retail store includes thousands of battery-powered ESL tags that are mostly connected wirelessly in a dense indoor environment. Raising the success ratio of wireless communication is essential for the system’s viability due to its limited battery life. Most of the ESL traffic is the image data of goods that appear on the tags, and reducing the amount of the data is one of the most effective ways to enhance communication performance and reduce retransmission. This paper proposes an ESL image compression mechanism based on chain coding that utilizes ESL images’ characteristics. The performance results show that the proposed mechanism could compress the ESL images smaller and decompress faster.
Highlights
The e-commerce market has grown rapidly due to improved Internet technology
Providing evaluation data of products to customers at offline stores has been possible with Electronic Shelf Labels (ESL) systems
RELATED WORKS Lossless image compression algorithms can be classified as follows [5], [7]: Run-Length Encoding (RLE) is an elementary form of lossless data compression that runs on sequences having the same value occurring many consecutive times, and it encodes the sequence to store only a single data value and its count
Summary
The e-commerce market has grown rapidly due to improved Internet technology. Many online shopping sites have emerged, and product evaluation services such as reviews and star ratings are found on most of them. The ability to change prices in realtime could allow retailers to adopt price strategies, such as changing prices based on the algorithms that consider competitor prices, supply and demand, and other external factors in the market. Because of these features, interests in ESL have been gradually increased around the world [3], [11]. The performance results show that our proposed compression algorithm could enhance the compression ratio and the decompression time than other algorithms.
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