Abstract: High precision equipment is often required in meat processing under ever-increasing livestock production at present. Current meat slicing equipment has also suffered from low slicing accuracy and high raw material loss, due to imaging occlusion during the quantitative slicing of irregular boneless meat. In contrast, the imaging after multi-view point cloud (Voint cloud) reconstruction is also plagued by high deployment costs and low adaptability to actual production scenarios. In this study, a high-precision quantitative slicing device was developed for pork loin using contour adaptive shaping. The pork loin was taken as the research object. The low imaging errors and high slicing accuracy were also obtained in the irregular meat products. (1) The device was composed of four components, including a scanning imaging unit, contour adaptive shaping, slicing execution, and a control system. The overall dimensions were defined to determine the key parameters. The effective range of shaping force F_min, F_max was derived for pork loin using force analysis. A shaping module was integrated with torque, force, and angle sensors to realize the adaptive closed-loop control of shaping parameters. (2) A PLC control system was constructed, including a perception subsystem with various sensors to acquire meat information and shaping motion data, a computing subsystem for image processing and path planning via a computer, and an execution subsystem for the movements of the shaping fixture and slicing mechanism. An adaptive motion of contour shaping and a non-equidistant slicing path planning were designed for the dynamic matching between the cutter and the conveyor belt speed. (3) Pork loin was used as the test sample to verify the actual performance of the shaping module and the slicing device. The conveyor belt and cutter speed matching test showed that the root mean square error (RMSE) of slicing positions ranged from 0.63 to 1.07 mm, and the mean absolute percentage error (MAPE) from 3.98% to 5.15%. There was a linear relationship (v=0.44M_e+16.10) between the set slicing weight M_e and the conveyor belt speed v, providing for an optimal speed matching scheme for different requirements of quantitative slicing. The verification of shaping effect indicated that the mean relative error (MRE) decreased from 11.13% to 6.24% in the quantitative slicing of pork loin after shaping treatment, whereas the qualification rate (q) increased from 70.12% to 91.43%, indicating an improvement of 4.89% in slicing accuracy and 21.31% in qualification rate, respectively. The optimal slicing effect was achieved in the 60° shaping angle, with the MRE of 6.61% and the q of 89.89%. The continuous slicing tests were conducted to verify the overall performance of the device with the set weights of 100 and 150 g. The slicing accuracy of chilled meat was superior to that of slightly frozen meat. In the quantitative slicing of 100 g chilled meat, the MAPE was 5.57%, and the q was 90.53%. In 150 g chilled meat, the MAPE was 5.11%, and the q was 89.69%. In view of the internal ice crystals and fiber breakage, the slightly frozen meat saw also shared an average increase of 0.76 g in RMSE and 0.84% in MAPE, where the q decreased by an average of 5.06%. The overall processing efficiency of the device reached 134 slices/min, fully meeting the demands of continuous production. In the stability test, the MRE of slicing with set weights of 70, 100, and 150 g ranged from 5.25% to 6.57%, and the coefficient of variation (CV) was all less than 10%, indicating excellent stability of the device. Contour adaptive shaping structure with multiple sensors reduced the slicing errors and raw material loss of conventional slicing equipment in irregular meat processing, thus promoting the transformation of the meat processing industry towards standardization and digitalization. The findings can provide technical references for high-precision quantitative slicing devices for irregular meat products.