###### Abstract  
In the domain of the Internet of Things (IoT), Optical Camera Communication (OCC) has garnered significant attention. This wireless technology employs solid-state lamps as transmitters and image sensors as receivers, offering a promising avenue for reducing energy costs and simplifying electronics. Moreover, image sensors are prevalent in various applications today, enabling dual functionality: recording and communication. However, a challenge arises when optical transmitters are not in close proximity to the camera, leading to sub-pixel projections on the image sensor and introducing strong channel dependence. Previous approaches, such as modifying camera optics or adjusting image sensor parameters, not only limited the camera's utility for purposes beyond communication but also made it challenging to accommodate multiple transmitters. In this paper, a novel sub-pixel optical transmitter discovery algorithm that overcomes these limitations is presented. This algorithm enables the use of OCC in scenarios with static transmitters and receivers without the need for camera modifications. This allows increasing the number of transmitters in a given scenario and alleviates the proximity and size limitations of the transmitters. Implemented in Python with multiprocessing programming schemes for efficiency, the algorithm achieved a 100% detection rate in nighttime scenarios, while there was a 89% detection rate indoors and a 72% rate outdoors during daylight. Detection rates were strongly influenced by varying transmitter types and lighting conditions. False positives remained minimal, and processing times were consistently under 1 s. With these results, the algorithm is considered suitable for export as a web service or as an intermediary component for data conversion into other network technologies. wireless sensor networks; optical camera communication; sub-pixel 2024243249103390/s24103249103390/10  
OWC has been reflected on the standardization efforts of the last years, e.g., IEEE 802.15.7r1, IEEE 802.11 bb, and ITU recommendation G.9991 [2]. In these standards, the focus extends to the two primary types of receivers commonly used in OWC: photodetectors and image sensors. On the one hand, photodetectors offer higher speeds, making them suitable for demanding applications. On the other hand, image sensors provide cost-effective solutions and spatial separation capabilities while maintaining the recording functionality. This last technology is known as OCC. OWC spans the electromagnetic spectrum from infrared to ultraviolet. However, it is the visible range that attracts the most interest due to the significant advancements in industrialization both in terms of transmitters and potential receivers. This technology is commonly referred to as Visible Light Communication (VLC). Consequently, there is a substantially broader range of publications in this area compared to the non-visible spectrum. This is particularly evident in fields related to sensor networks and IoT, driven by the low costs associated with advancements mentioned in commercialization and industrialization, as can be seen for example in [3]. The emphasis on the visible spectrum is also observed in OCC for similar reasons. Nevertheless, it is noteworthy that many cameras also operate within the infrared spectrum, so this range can also be exploited at low cost and with less visual impact in the scenarios where communication systems are installed. In the domain of OCC, two acquisition modes are usually available among commercial image sensors, as also detailed in the aforementioned standards: Global Shutter (GS) and Rolling Shutter (RS). Whilst GS utilizes Charge-Coupled Device (CCD) sensors, enabling the simultaneous capture of all pixels, Rolling Shutter (RS) systems, primarily based on Complementary Metal-Oxide-Semiconductor (CMOS) technology, capture pixels sequentially rather than all at once, processing the images row by row.