In the past few years, the demand for intelligence of IoT front-end devices has dramatically increased. However, such devices face challenges of limited on-chip resources and strict power or energy constraints. Recent progress in binarized neural networks has provided promising solutions for front-end processing system to conduct simple detection and classification tasks by making trade-offs between the processing quality and the computation complexity. In this paper, we propose a mixed-signal perception chip, in which an ADC-free 32×32 image sensor and a BNN processing array are directly integrated with a 180nm standard CMOS process. Taking advantage of the ADC-free processing architecture, the whole processing system only consumes 1.8mW power, while providing up to 545.4 GOPS/W energy efficiency. The implementation performance and energy efficiency are comparable with the state-of-the-art designs in much more advanced CMOS technologies. This work provides a promising alternative for low-power IoT intelligent applications.