【机器视觉】 fuzzy_measure_pairing算子
00. 目錄
文章目錄
- 00. 目錄
- 01. 概述
- 02. 簽名
- 03. 描述
- 04. 注意
- 05. 參數
- 06. 結果
- 07. 附錄
01. 概述
fuzzy_measure_pairing - 提取垂直于矩形或環形弧的直邊對。
02. 簽名
fuzzy_measure_pairs(Image : : MeasureHandle, Sigma, AmpThresh, FuzzyThresh, Transition : RowEdgeFirst, ColumnEdgeFirst, AmplitudeFirst, RowEdgeSecond, ColumnEdgeSecond, AmplitudeSecond, RowEdgeCenter, ColumnEdgeCenter, FuzzyScore, IntraDistance, InterDistance)
03. 描述
fuzzy_measure_pairing用于提取垂直于矩形或環形弧長軸的直邊對。
提取算法與fuzzy_measure_pairs相同，但也可以使用參數Pairing提取交織和包含對。 目前只有’no_restriction’可用，它返回所有可能的邊緣對，允許交叉和包含對。
NumPairs只返回得分最高的邊緣對個數，而0表示返回所有可能的邊緣組合。
選定的邊將作為單個點返回，這些點位于矩形或環形弧的長軸上。 相應的邊緣振幅在AmplitudeFirst和AmplitudeSecond中返回，FuzzyScore表示模糊分數。 另外，每個邊緣對之間的距離在IntraDistance中返回，對應于EdgeFirst [i]和EdgeSecond [i]之間的距離。
原文描述：
fuzzy_measure_pairs serves to extract straight edge pairs which lie perpendicular to the major axis of a rectangle or an annular arc. In addition to measure_pairs it uses fuzzy functions to evaluate and select the edge pairs.
For an explanation of the concept of 1D measuring see the introduction of chapter 1D Measuring.
The extraction algorithm of fuzzy_measure_pairs is identical to fuzzy_measure_pos. In addition, neighboring edges are grouped to pairs. To extract pairs that intersect or include each other, use fuzzy_measure_pairing.
If Transition = ‘positive’, the edge points with a dark-to-light transition in the direction of the major axis of the rectangle or annular arc are returned in RowEdgeFirst and ColumnEdgeFirst. In this case, the corresponding edges with a light-to-dark transition are returned in RowEdgeSecond and ColumnEdgeSecond. If Transition = ‘negative’, the behavior is exactly opposite. If Transition = ‘all’, the first detected edge defines the transition for RowEdgeFirst and ColumnEdgeFirst. I.e., dependent on the positioning of the measure object, edge pairs with a light-dark-light transition or edge pairs with a dark-light-dark transition are returned. This is suited, e.g., to measure objects with different brightness relative to the background.
Having extracted subpixel edge locations, the edges are paired. The pairing algorithm groups the edges such that interleavings and inclusions of pairs are prohibited. The features of an edge pair are evaluated by a fuzzy function, which can be set by set_fuzzy_measure or set_fuzzy_measure_norm_pair. Which edge pairs are selected can be determined with the parameter FuzzyThresh, which constitutes a threshold on the weight over all fuzzy sets, i.e., the geometric mean of the weights of the defined fuzzy functions.
The selected edges are returned as single points, which lie on the major axis of the rectangle or annular arc. The corresponding edge amplitudes are returned in AmplitudeFirst and AmplitudeSecond, the fuzzy scores in FuzzyScore. In addition, the distance between each edge pair is returned in IntraDistance and the distance between consecutive edge pairs is returned in InterDistance. Here, IntraDistance[i] corresponds to the distance between EdgeFirst[i] and EdgeSecond[i], while InterDistance[i] corresponds to the distance between EdgeSecond[i] and EdgeFirst[i+1], i.e., the tuple InterDistance contains one element less than the tuples of the edge pairs.
執行信息
● 多線程類型：可重入（與非獨占算子并行運行）。
● 多線程范圍：全局（可以從任何線程調用）。
● 不并行處理。
04. 注意
? 只有邊緣是直的并且垂直于矩形或環形弧的長軸，fuzzy_measure_pairing返回的結果才有意義。 因此，它不應該用于從曲面對象中提取邊緣。 此外，用戶應確保矩形或環形弧盡可能接近垂直于圖像的邊緣。 此外，西格瑪不能大于約0.5 *Length1（對于Length1請參見gen_measure_rectangle2）。
應該記住，為了效率的原因，fuzzy_measure_pairing會忽略Image的ROI域。 如果圖像中的特定區域應該從measurement中排除，則應該生成具有適當修改的參數的新measure對象。
05. 參數
Image (input_object) 單通道圖像 → object (byte / uint2 / real)
輸入圖像。
MeasureHandle (input_control) measure_id → (integer)
measure對象的句柄。
Sigma (input_control) number → (real)
高斯平滑的Sigma。
Default value: 1.0
Suggested values: 0.4, 0.6, 0.8, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0
Typical range of values: 0.4 ≤ Sigma ≤ 100 (lin)
Minimum increment: 0.01
Recommended increment: 0.1
Restriction: Sigma >= 0.4
AmpThresh (input_control) number → (real)
最小邊緣幅度。
Default value: 30.0
Suggested values: 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 90.0, 110.0
Typical range of values: 1 ≤ AmpThresh ≤ 255 (lin)
Minimum increment: 0.5
Recommended increment: 2
FuzzyThresh (input_control) number → (real)
最小模糊值。
Default value: 0.5
Suggested values: 0.1, 0.3, 0.5, 0.7, 0.9
Typical range of values: 0.0 ≤ FuzzyThresh ≤ 1.0 (lin)
Recommended increment: 0.1
Transition (input_control) string → (string)
選擇邊緣對的第一個灰度值轉換。
Default value: ‘all’
List of values: ‘all’, ‘negative’, ‘positive’
Pairing (input_control) string → (string)
配對約束。
Default value: ‘no_restriction’
List of values: ‘no_restriction’
NumPairs (input_control) number → (integer)
邊緣對的數量。
Default value: 10
Suggested values: 0, 1, 10, 20, 50
Typical range of values: 0 ≤ NumPairs
Recommended increment: 1
RowEdgeFirst (output_control) point.y-array → (real)
（邊緣對）第一條邊的Row坐標。
ColumnEdgeFirst (output_control) point.x-array → (real)
（邊緣對）第一條邊的Column坐標。
AmplitudeFirst (output_control) real-array → (real)
（邊緣對）第一個邊的邊緣幅度（帶符號）。
RowEdgeSecond (output_control) point.y-array → (real)
（邊緣對）第二個邊的Row坐標。
ColumnEdgeSecond (output_control) point.x-array → (real)
（邊緣對）第二個邊的Column坐標。
AmplitudeSecond (output_control) real-array → (real)
（邊緣對）第二個邊緣的邊緣幅度（帶符號）。
RowPairCenter (output_control) point.y-array → (real)
邊緣對的中心的Row坐標。
ColumnPairCenter (output_control) point.x-array → (real)
邊緣對的中心的Column坐標。
FuzzyScore (output_control) real-array → (real)
邊緣對的模糊評估分數。
IntraDistance (output_control) real-array → (real)
邊緣對內的距離。
06. 結果
如果參數值正確，則算子fuzzy_measure_pairing將返回值2（H_MSG_TRUE）。 否則會引發異常。
HDevelop例程
inspect_bottle_label_360_degree.hdev 將一個瓶子的四個圖像組合成拼接圖像，顯示瓶子的標簽展開圖。
程序示例
07. 附錄
7.1 機器視覺博客匯總
網址：https://dengjin.blog.csdn.net/article/details/116837497
總結
以上是生活随笔為你收集整理的【机器视觉】 fuzzy_measure_pairing算子的全部內容，希望文章能夠幫你解決所遇到的問題。
- 上一篇： 【机器视觉】 deserialize_m
- 下一篇： 【机器视觉】 fuzzy_measure