Optimization of Face Retrieval and Real Time Face Recognition Systems Using Heuristic Indexing

Sawat, Dattatray D.; Santosh, K. C.; Hegadi, Ravindra S.

doi:10.1007/978-981-16-0507-9_7

Cited by 1 publication

(1 citation statement)

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“…Sukhjeet et al [32] used a hybrid approach which utilizes color space and quaternion moment vector to create this unique feature vector. Sawat et al [33] used a heuristic approach for real-time content-based images retrieval. Qin et al [34] used local gradient of images to extract the directional gradient feature vector and tested their approach on six different datasets.…”

Section: State Of the Artmentioning

confidence: 99%

PCA-Based Advanced Local Octa-Directional Pattern (ALODP-PCA): A Texture Feature Descriptor for Image Retrieval

et al. 2022

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This paper presents a novel feature descriptor termed principal component analysis (PCA)-based Advanced Local Octa-Directional Pattern (ALODP-PCA) for content-based image retrieval. The conventional approaches compare each pixel of an image with certain neighboring pixels providing discrete image information. The descriptor proposed in this work utilizes the local intensity of pixels in all eight directions of its neighborhood. The local octa-directional pattern results in two patterns, i.e., magnitude and directional, and each is quantized into a 40-bin histogram. A joint histogram is created by concatenating directional and magnitude histograms. To measure similarities between images, the Manhattan distance is used. Moreover, to maintain the computational cost, PCA is applied, which reduces the dimensionality. The proposed methodology is tested on a subset of a Multi-PIE face dataset. The dataset contains almost 800,000 images of over 300 people. These images carries different poses and have a wide range of facial expressions. Results were compared with state-of-the-art local patterns, namely, the local tri-directional pattern (LTriDP), local tetra directional pattern (LTetDP), and local ternary pattern (LTP). The results of the proposed model supersede the work of previously defined work in terms of precision, accuracy, and recall.

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Section: State Of the Artmentioning

confidence: 99%