Multi technique amalgamation for enhanced information identification with content based image data

Das, Rik; Thepade, Sudeep D.; Ghosh, Swaroop

doi:10.1186/s40064-015-1515-4

“…Table V The results and comparisons presented in Fig. 9 and Table V indicate that the proposed late fusion of FREAK and SIFT provides a better retrieval performance than existing research [26], [38].…”

Section: Performance Evaluation Using Oliva and Torralba (Ot-scene)mentioning

confidence: 80%

“…8 represents a sample of randomly selected images from each class of the OT-Scene image dataset. We evaluated the proposed framework using OT-Scene benchmark and compared the results with state-of-the-art CBIR methods [26], [38]. Fig.…”

Section: Performance Evaluation Using Oliva and Torralba (Ot-scene)mentioning

confidence: 99%

Content-Based Image Retrieval Based on Late Fusion of Binary and Local Descriptors

Ali¹,

Mazhar²,

Iqbal³

et al. 2017

Preprint

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One of the challenges in Content-Based Image Retrieval (CBIR) is to reduce the semantic gaps between low-level features and high-level semantic concepts. In CBIR, the images are represented in the feature space and the performance of CBIR depends on the type of selected feature representation.Late fusion also known as visual words integration is applied to enhance the performance of image retrieval. The recent advances in image retrieval diverted the focus of research towards the use of binary descriptors as they are reported computationally efficient. In this paper, we aim to investigate the late fusion of Fast Retina Keypoint (FREAK) and Scale Invariant Feature Transform (SIFT). The late fusion of binary and local descriptor is selected because among binary descriptors, FREAK has shown good results in classification-based problems while SIFT is robust to translation, scaling, rotation and small distortions. The late fusion of FREAK and SIFT integrates the performance of both feature descriptors for an effective image retrieval. Experimental results and comparisons show that the proposed late fusion enhances the performances of image retrieval.

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“…Table V The results and comparisons presented in Fig. 9 and Table V indicate that the proposed late fusion of FREAK and SIFT provides a better retrieval performance than existing research [30], [42].…”

Section: Performance Evaluation Using Oliva and Torralba (Ot-scene)mentioning

confidence: 80%

“…8 represents a sample of randomly selected images from each class of the OT-Scene image dataset. We evaluated the proposed framework using OT-Scene benchmark and compared the results with state-of-the-art CBIR methods [30], [42]. Fig.…”

Section: Performance Evaluation Using Oliva and Torralba (Ot-scene)mentioning

confidence: 99%

Content-Based Image Retrieval Based on Late Fusion of Binary and Local Descriptors

Ali¹,

Mazhar²,

Iqbal³

et al. 2017

Preprint

View full text Add to dashboard Cite

One of the challenges in Content-Based Image Retrieval (CBIR) is to reduce the semantic gaps between low-level features and high-level semantic concepts. In CBIR, the images are represented in the feature space and the performance of CBIR depends on the type of selected feature representation.Late fusion also known as visual words integration is applied to enhance the performance of image retrieval. The recent advances in image retrieval diverted the focus of research towards the use of binary descriptors as they are reported computationally efficient. In this paper, we aim to investigate the late fusion of Fast Retina Keypoint (FREAK) and Scale Invariant Feature Transform (SIFT). The late fusion of binary and local descriptor is selected because among binary descriptors, FREAK has shown good results in classification-based problems while SIFT is robust to translation, scaling, rotation and small distortions. The late fusion of FREAK and SIFT integrates the performance of both feature descriptors for an effective image retrieval. Experimental results and comparisons show that the proposed late fusion enhances the performances of image retrieval.

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“…The differences in matching success between our visual and automated results, and the advantages of automated methods using large sets of images suggest that additional progress in automated image recognition may prove beneficial. For example, through the use of biometrics (Kühl and Burghardt 2013), in combination with several image identification techniques to improve matching success (e.g., Das et al 2015). Although preliminary recognition for uncropped head images of delta smelt using TinEye showed the matching success did not significantly increase compared to images of cropped head areas B − C (Tien-Chieh Hung, UC Davis FCCL, unpubl.…”

Section: Photo Sessions Low-light N High-light N Low-light Proportionmentioning

confidence: 99%

Evaluation of chromatophores as natural marks for delta smelt: the effects of life-stage and light intensity

Castillo

¹

,

Sandford

²

,

Hung

³

et al. 2019

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Individual identification of small sized fishes such as the endangered delta smelt Hypomesus transpacificus remains a pressing need. We evaluated the stability of chromatophores as potential natural marks for subadult and adult delta smelt under low and high ambient light. We conducted three photo sessions of the dorsal head area at about three month intervals from fall 2014 to spring 2015. Image recognition was performed using visual tests (naked eye) and automated image recognition (TinEye's Match Engine). The stability of chromatophores between sessions was independently evaluated using: 1) the percent of correct matching (matching success), 2) similarity indices between matched images (match quality), and 3) the change in their relative size (chromatophore expression). Matching success (mean ± SD) was higher for visual tests (86 ± 12%) than automated tests (44 ± 30%), and was consistently higher from winter to spring for both visual (100%) and automated tests (80 ± 16%). Unlike visual tests, automated matching success differed between light treatments from winter to spring, and automated match quality was higher under low ambient light. Chromatophore expression increased between fall and winter, and decreased between winter and spring in both genders. Ambient light was less influential on matching success than ontogenetic changes between the subadult and adult stages. These results suggest chromatophores of delta smelt are more stable and have higher potential for practical use of natural marks under a wide range of ambient light scenarios when the adult stage is reached.

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Multi technique amalgamation for enhanced information identification with content based image data

Cited by 8 publications

References 42 publications

Content-Based Image Retrieval Based on Late Fusion of Binary and Local Descriptors

Content-Based Image Retrieval Based on Late Fusion of Binary and Local Descriptors

Content-Based Image Retrieval Based on Late Fusion of Binary and Local Descriptors

Evaluation of chromatophores as natural marks for delta smelt: the effects of life-stage and light intensity

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