# Key Region Extraction and Body Dimension Measurement of Beef Cattle Using 3D Point Clouds

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## Abstract

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## 1. Introduction

## 2. Materials and Methods

#### 2.1. Acquisition of Beef Cattle Point Cloud Data

#### 2.2. Definition of Beef Cattle Body Dimensions

#### 2.3. Algorithm for Beef Cattle Body Dimension Calculation

#### 2.4. Identification of Point Clouds of Leg Regions

#### 2.4.1. Extraction of Continuous Slices and Span Characteristic Curves

#### 2.4.2. Location of the Leg Region

_{max}is the span value of the range domain for the fitted curve, x

_{max}is the span value of the domain of the fitted curve, and X

_{1}and X

_{2}represent the x-coordinate values of the approximate midpoint in the leg region.

_{i}represents the discrete point on the distribution curve of span values. According to the independent variables in ascending order, the average gradient distribution of all the “five-point clusters” on the curve (Figure 5) was sequentially extracted, as shown in Figure 7. The gradient characteristic distribution curve (blue curve in Figure 7) shows that the maximum value (black dot) and the minimum value (red dot) appear at the boundary of the leg region, which is consistent with the geometric distribution characteristics of beef cattle point cloud slices. Therefore, the two points with the maximum gradient were selected as the starting boundary positions for regional segmentation. The two points with the minimum gradient were selected as the ending boundary positions, highlighted by the red dotted line in Figure 7. Each central point of the leg, along with the starting and ending boundaries, forms the regions of the forelegs and hind legs, which means that the automatic extraction of the leg region is implemented.

#### 2.4.3. Calibration of Boundaries for the Leg Region

_{1}_1 and x

_{1}_2 represent the x-coordinates of the front and back boundaries of the foreleg region before calibration, x

_{2}_1 and x

_{2}_2 represent the x-coordinates of the front and back boundaries of the hind leg region after calibration, p is the x-coordinate corresponding to the boundary of the leg region after calibration, and n is the number of clusters derived from the DBSCAN clustering algorithm.

#### 2.5. Extraction of the Key Regions for Body Dimension Calculation

#### 2.5.1. Determination of the Longitudinal Cutting Plane

#### 2.5.2. Determination of the Horizontal Cutting Plane

#### 2.5.3. Extraction of Key Regions

#### 2.6. Extraction of the Key Regions for Body Dimension Calculation

#### 2.6.1. Body Oblique Length

#### 2.6.2. Body Width

#### 2.6.3. Wither Height

#### 2.6.4. Chest and Abdominal Girth

## 3. Results

#### 3.1. Results of Locating Key Regions

#### 3.2. Body Measurement Results

## 4. Discussion

#### 4.1. The Error Analysis of Body Width

#### 4.2. The Error Analysis of Wither Height

#### 4.3. The Error Analysis of Body Oblique Length

#### 4.4. The Error Analysis of Chest and Abdomen Girth

## 5. Conclusions

- (1)
- Based on the span distribution curve of continuous slices, a method for identifying the position and boundary of the leg region was proposed, and a method for key region extraction in the leg region was proposed to calculate the body dimensions. The shoulder, chest, abdomen, and buttock regions were accurately identified and extracted.
- (2)
- Based on the features of the key regions, the body oblique length, wither height, body width, chest girth, and abdominal girth were calculated, and the average measurement errors were 2.3%, 2.8%, 1.6%, 2.8%, and 2.6%, respectively. Compared with the method based on the “point” features, this method, focusing on the “region” features, is more suitable to deal with incomplete point clouds and poses limited requirements regarding animal postures, which shows its higher robustness.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Beef cattle point cloud data acquisition equipment (

**a**), user interface (

**b**), and examples of collected point cloud data (front view (

**c**,

**d**), top view (

**e**)).

**Figure 8.**The errors arising from boundary calibration for beef cattle leg region. ((

**a**) Broadened foreleg region, (

**b**) broadened hind leg region, (

**c**) broadened regions of forelegs and hind legs).

**Figure 9.**The longitudinal slices of beef cattle point clouds with the inflated and calibrated boundaries of the same leg regions. (

**a**) The slice with the broadened width, (

**b**) the slice with the desired width.

**Figure 13.**The results of key region extraction for (

**a**) the original beef cattle point clouds and (

**b**) the extracted regions for body dimension calculation.

**Figure 16.**The error distribution of each body dimension (calculated for 182 sets of point clouds corresponding to 10 beef cattle).

**Figure 21.**Two enlarged wither height cases. ((

**a**) Animal with an arched back, (

**b**) animal with hair lift).

Parameters | Symbol | Measurement Standard |
---|---|---|

Wither height | BH | The length of the vertical line from the beef stinger to the ground |

Body oblique length | BL | Distance from shoulder to the ischial end of beef cattle |

Body width | BW | Maximum horizontal width at beef wither |

Chest girth | BC | Perimeter of the vertical body axis at the back of the wither |

Abdominal girth | BS | Maximum vertical circumference of the belly of beef cattle |

Beef Cattle Id | Oblique Length | Body Width | Wither Height | Chest Girth | Abdominal Girth | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

M | A | E | M | A | E | M | A | E | M | A | E | M | A | E | |

1 | 160 | 158 | 2.8% | 47 | 47 | 2.6% | 130 | 129 | 3.0% | 184 | 188 | 3.0% | 208 | 213 | 3.0% |

2 | 158 | 158 | 2.4% | 45 | 45 | 1.5% | 133 | 133 | 2.4% | 195 | 199 | 2.9% | 209 | 212 | 2.6% |

3 | 159 | 159 | 2.1% | 43 | 43 | 1.5% | 131 | 132 | 2.5% | 182 | 187 | 3.4% | 192 | 197 | 3.1% |

4 | 156 | 157 | 2.2% | 46 | 46 | 1.3% | 129 | 129 | 3.3% | 182 | 183 | 2.3% | 201 | 204 | 2.5% |

5 | 162 | 160 | 3.0% | 36 | 36 | 2.2% | 132 | 133 | 2.5% | 165 | 170 | 3.6% | 193 | 197 | 2.8% |

6 | 157 | 157 | 2.5% | 39 | 39 | 1.7% | 125 | 125 | 2.7% | 158 | 160 | 2.8% | 196 | 200 | 2.7% |

7 | 169 | 168 | 2.4% | 44 | 45 | 1.3% | 130 | 131 | 2.9% | 185 | 189 | 2.9% | 223 | 228 | 3.1% |

8 | 147 | 149 | 2.4% | 48 | 48 | 0.8% | 127 | 129 | 3.4% | 192 | 197 | 3.3% | 204 | 210 | 2.9% |

9 | 153 | 152 | 2.2% | 39 | 39 | 1.7% | 124 | 124 | 2.6% | 169 | 173 | 3.5% | 189 | 192 | 2.5% |

10 | 155 | 158 | 2.5% | 38 | 38 | 2.0% | 123 | 126 | 3.9% | 164 | 166 | 1.8% | 190 | 191 | 2.0% |

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**MDPI and ACS Style**

Li, J.; Li, Q.; Ma, W.; Xue, X.; Zhao, C.; Tulpan, D.; Yang, S.X.
Key Region Extraction and Body Dimension Measurement of Beef Cattle Using 3D Point Clouds. *Agriculture* **2022**, *12*, 1012.
https://doi.org/10.3390/agriculture12071012

**AMA Style**

Li J, Li Q, Ma W, Xue X, Zhao C, Tulpan D, Yang SX.
Key Region Extraction and Body Dimension Measurement of Beef Cattle Using 3D Point Clouds. *Agriculture*. 2022; 12(7):1012.
https://doi.org/10.3390/agriculture12071012

**Chicago/Turabian Style**

Li, Jiawei, Qifeng Li, Weihong Ma, Xianglong Xue, Chunjiang Zhao, Dan Tulpan, and Simon X. Yang.
2022. "Key Region Extraction and Body Dimension Measurement of Beef Cattle Using 3D Point Clouds" *Agriculture* 12, no. 7: 1012.
https://doi.org/10.3390/agriculture12071012