Silkworm Eggs Counting System Using Image Processing Algorithm

Pathan, Sanaha S.; Harale, Avinash D.

doi:10.1007/978-3-319-53556-2_32

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Fish farmers have a lot of works to do [6] especially egg counting [7] fish that requires accuracy. The right method is needed so that the calculation process takes place quickly and correctly.…”

Section: Related Workmentioning

confidence: 99%

Fish Eggs Calculation Models Using Morphological Operation

Ramdhan¹,

Syafrullah²

2019

EECSI

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Calculations on group objects are the concern of current researchers, to find optimal detection and calculation solutions. One of them is fish eggs in a group. Fish cultivators need precision in calculations, because currently conventional methods often make errors in calculations. If the calculation is wrong, it will have an impact on production and sales that are not balanced (loss). Small and easily broken fish eggs are grouped and it is difficult to do manual calculations. The purpose of this study is to test which segmentation method is the most optimal in calculating these grouped fish egg objects and produce precise and fast calculations. The test model was developed from algorithm of morphological operations, watershed and statistical approaches with the same number of samples. The result shows morphological operation is better than the others with 96.67%, watershed 81.28% and the count statistic is 95.62% with an average calculation process speed of 54.5 seconds for morphological operations, watershed 1 minute 55 seconds and statistical approach 58.9 seconds. As a result. morphology gets the most optimal and fast calculation results.

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Section: Related Workmentioning

confidence: 99%

Fish Eggs Calculation Models Using Morphological Operation

Ramdhan¹,

Syafrullah²

2019

EECSI

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“…Success of sericulture as a cash crop depends on the vitality and robustness of silkworm seed (egg) supplied to the farmers (Narasimhanna, 1988;Singh, 2010;Pathan & Harale, 2016). Quality silkworm seed or egg is the backbone of the sericulture industry.…”

Section: Introductionmentioning

confidence: 99%

Productive Performance of Philippine Silkworm (Bombyx Mori L.) Purelines Fed with Folic Acid-Enriched Mulberry Leaves

2024

Int. J. Biosci.

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Low silk production has been attributed to the low quality of mulberry leaves fed to silkworms during rearing.Thus, quality of mulberry leaves should be enhanced. This study determined the efficacy of folic acid-enriched mulberry leaves in the performance of silkworms and silkmoth egg production. Fifth instar larvae of the six (6) silkworm purelines were used in the study. Mulberry leaves were supplemented with 0.001% Folic Acid (T1) and 0 .002% Folic Acid (T2) and compared to the Control (No Supplementation). Results showed that the larvae, cocoons and eggs produced by the silkworm purelines fed with folic acid supplemented mulberry leaves were significantly affected based on the weight of 10 matured larvae, single shell weight, single cocoon weight, effective rearing rate (ERR), cocoon yield per box (CYPB), and fecundity. An interaction effect on the effective rearing rate (ERR) and cocoon yield per box (CYPB) from silkworm fed with folic acid supplemented mulberry leaves revealed significant differences among all treatments and breeds. It can be noted that folic acid-enriched mulberry leaves fed to silkworms tend to have higher results as compared to the control treatment (CT) on all the parameters of the study.

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An egg image noise model for digital visual counting processing

Behaine

Ide

2021

2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)

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Silkworm Eggs Counting System Using Image Processing Algorithm

Cited by 3 publications

References 7 publications

Fish Eggs Calculation Models Using Morphological Operation

Fish Eggs Calculation Models Using Morphological Operation

Productive Performance of Philippine Silkworm (Bombyx Mori L.) Purelines Fed with Folic Acid-Enriched Mulberry Leaves

An egg image noise model for digital visual counting processing

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